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USER ACTIVITY TRACKING USING WEB LOG DATA  MINING
 
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Implement a data mining approach in order to increase the revenue generation by analysing the users browsing behaviour for the TCP Training Company’s website based on their web log data.
Views: 578 Bajju Sampath
Introduction to Event Log Mining with R
 
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Event logs are everywhere and represent a prime source of Big Data. Event log sources run the gamut from e-commerce web servers to devices participating in globally distributed Internet of Things (IoT) architectures. Even Enterprise Resource Planning (ERP) systems produce event logs! Given the rich and varied data contained in event logs, mining these assets is a critical skill needed by every Data Scientist, Business/Data Analyst, and Program/Product Manager. At this meetup, presenter Dave Langer, will show how easy it is to get started mining your event logs using the OSS tools of R and ProM. Dave will cover the following during the presentation: • The scenarios and benefits of event log mining • The minimum data required for event log mining • Ingesting and analyzing event log data using R • Process Mining with ProM • Event log mining techniques to create features suitable for Machine Learning models • Where you can learn more about this very handy set of tools and techniques *R source code will be made available via GitHub here: https://github.com/EasyD/IntroToEventLogMiningMeetup Find out more about David here: https://www.meetup.com/data-science-dojo/events/235913034/ -- Learn more about Data Science Dojo here: http://bit.ly/2lZC5jq -- Like Us: https://www.facebook.com/datasciencedojo/ Follow Us: https://twitter.com/DataScienceDojo Connect with Us: https://www.linkedin.com/company/data-science-dojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo/ Vimeo: https://vimeo.com/datasciencedojo
Views: 5198 Data Science Dojo
Mining Your Logs - Gaining Insight Through Visualization
 
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Google Tech Talk (more info below) March 30, 2011 Presented by Raffael Marty. ABSTRACT In this two part presentation we will explore log analysis and log visualization. We will have a look at the history of log analysis; where log analysis stands today, what tools are available to process logs, what is working today, and more importantly, what is not working in log analysis. What will the future bring? Do our current approaches hold up under future requirements? We will discuss a number of issues and will try to figure out how we can address them. By looking at various log analysis challenges, we will explore how visualization can help address a number of them; keeping in mind that log visualization is not just a science, but also an art. We will apply a security lens to look at a number of use-cases in the area of security visualization. From there we will discuss what else is needed in the area of visualization, where the challenges lie, and where we should continue putting our research and development efforts. Speaker Info: Raffael Marty is COO and co-founder of Loggly Inc., a San Francisco based SaaS company, providing a logging as a service platform. Raffy is an expert and author in the areas of data analysis and visualization. His interests span anything related to information security, big data analysis, and information visualization. Previously, he has held various positions in the SIEM and log management space at companies such as Splunk, ArcSight, IBM research, and PriceWaterhouse Coopers. Nowadays, he is frequently consulted as an industry expert in all aspects of log analysis and data visualization. As the co-founder of Loggly, Raffy spends a lot of time re-inventing the logging space and - when not surfing the California waves - he can be found teaching classes and giving lectures at conferences around the world. http://about.me/raffy
Views: 24926 GoogleTechTalks
What is CLICKSTREAM? What does CLICKSTREAM mean? CLICKSTREAM meaning, definition & explanation
 
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What is CLICKSTREAM? What does CLICKSTREAM mean? CLICKSTREAM meaning - CLICKSTREAM pronunciation - CLICKSTREAM definition - CLICKSTREAM explanation - How to pronounce CLICKSTREAM? Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. SUBSCRIBE to our Google Earth flights channel - https://www.youtube.com/channel/UC6UuCPh7GrXznZi0Hz2YQnQ A clickstream is the recording of the parts of the screen a computer user clicks on while web browsing or using another software application. As the user clicks anywhere in the webpage or application, the action is logged on a client or inside the web server, as well as possibly the web browser, router, proxy server or ad server. Clickstream analysis is useful for web activity analysis, software testing, market research, and for analyzing employee productivity. Initial clickstream or click path data had to be gleaned from server log files. Because human and machine traffic were not differentiated, the study of human clicks took a substantial effort. Subsequently, Javascript technologies were developed which use a tracking cookie to generate a series of signals from browsers. In other words, information was only collected from "real humans" clicking on sites through browsers.It was not possible to identify the clickpath. A clickstream is a series of page requests, every page requested generates a signal. These signals can be graphically represented for clickstream reporting. The main point of clickstream tracking is to give webmasters insight into what visitors on their site are doing. This data itself is "neutral" in the sense that any dataset is neutral. The data can be used in various scenarios, one of which is marketing. Additionally, any webmaster, researcher, blogger or person with a website can learn about how to improve their site. Use of clickstream data can raise privacy concerns, especially since some Internet service providers have resorted to selling users' clickstream data as a way to enhance revenue. There are 10-12 companies that purchase this data, typically for about $0.40/month per user. While this practice may not directly identify individual users, it is often possible to indirectly identify specific users, an example being the AOL search data scandal. Most consumers are unaware of this practice, and its potential for compromising their privacy. In addition, few ISPs publicly admit to this practice. Analyzing the data of clients that visit a company website can be important in order to remain competitive. This analysis can be used to generate two findings for the company, the first being an analysis of a user’s clickstream while using a website to reveal usage patterns, which in turn gives a heightened understanding of customer behaviour. This use of the analysis creates a user profile that aids in understanding the types of people that visit a company’s website. As discussed in Van den Poel & Buckinx (2005), clickstream analysis can be used to predict whether a customer is likely to purchase from an e-commerce website. Clickstream analysis can also be used to improve customer satisfaction with the website and with the company itself. This can generate a business advantage, and be used to assess the effectiveness of advertising on a web page or site. Data mining, column-oriented DBMS, and integrated OLAP systems can be used in conjunction with clickstreams to better record and analyze this data. Clickstreams can also be used to allow the user to see where they have been and allow them to easily return to a page they have already visited, a function that is already incorporated in most browsers. Unauthorized clickstream data collection is considered to be spyware. However, authorized clickstream data collection comes from organizations that use opt-in panels to generate market research using panelists who agree to share their clickstream data with other companies by downloading and installing specialized clickstream collection agents.
Views: 483 The Audiopedia
Intro and Getting Stock Price Data - Python Programming for Finance p.1
 
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Welcome to a Python for Finance tutorial series. In this series, we're going to run through the basics of importing financial (stock) data into Python using the Pandas framework. From here, we'll manipulate the data and attempt to come up with some sort of system for investing in companies, apply some machine learning, even some deep learning, and then learn how to back-test a strategy. I assume you know the fundamentals of Python. If you're not sure if that's you, click the fundamentals link, look at some of the topics in the series, and make a judgement call. If at any point you are stuck in this series or confused on a topic or concept, feel free to ask for help and I will do my best to help. https://pythonprogramming.net https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex
Views: 199342 sentdex
K-Means Clustering Algorithm - Cluster Analysis | Machine Learning Algorithm | Data Science |Edureka
 
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( Data Science Training - https://www.edureka.co/data-science ) This Edureka k-means clustering algorithm tutorial video (Data Science Blog Series: https://goo.gl/6ojfAa) will take you through the machine learning introduction, cluster analysis, types of clustering algorithms, k-means clustering, how it works along with an example/ demo in R. This Data Science with R tutorial video is ideal for beginners to learn how k-means clustering work. You can also read the blog here: https://goo.gl/QM8on4 Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS #kmeans #clusteranalysis #clustering #datascience #machinelearning How it Works? 1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. You will get Lifetime Access to the recordings in the LMS. 4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities. - - - - - - - - - - - - - - Why Learn Data Science? Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework. After the completion of the Data Science course, you should be able to: 1. Gain insight into the 'Roles' played by a Data Scientist 2. Analyse Big Data using R, Hadoop and Machine Learning 3. Understand the Data Analysis Life Cycle 4. Work with different data formats like XML, CSV and SAS, SPSS, etc. 5. Learn tools and techniques for data transformation 6. Understand Data Mining techniques and their implementation 7. Analyse data using machine learning algorithms in R 8. Work with Hadoop Mappers and Reducers to analyze data 9. Implement various Machine Learning Algorithms in Apache Mahout 10. Gain insight into data visualization and optimization techniques 11. Explore the parallel processing feature in R - - - - - - - - - - - - - - Who should go for this course? The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics 4. Business Analysts who want to understand Machine Learning (ML) Techniques 5. Information Architects who want to gain expertise in Predictive Analytics 6. 'R' professionals who want to captivate and analyze Big Data 7. Hadoop Professionals who want to learn R and ML techniques 8. Analysts wanting to understand Data Science methodologies Please write back to us at [email protected] or call us at +918880862004 or 18002759730 for more information. Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Reviews: Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best. "
Views: 49228 edureka!
data mining technology
 
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Make an animated explainer video for free at: http://www.rawshorts.com Now you create your own explainer videos and animated presentations for free. Raw Shorts is a free cloud based video builder that allows you to make awesome explanation videos for your business, website, startup video, pitch video, product launch, video resume, landing page video or anything else you could use an animated explainer video. Our free video templates and explainer video software will help you create presentation videos in an instant! It's never been easier to make an animated explainer video with outstanding production value and without the cost or hassle of hiring an expensive production company or animation studio. Wait no more! Our animation software is free to use. You can make an animated video today for your landing page, website, kickstarter video, indiegogo video, pitch video and more. Simply log on and select from thousands of animated icons, animated characters and free video templates for business to make the perfect web video for your business.
Views: 435 jojo20
Customer Segmentation Using Log Data (Click Stream Analytics) - Happiest Minds
 
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In this video, a case study explained on how Happiest Minds helped an ecommerce company identifying right customer segments using click stream analytics Want to learn more about Click Stream Data Analytics? Watch this video https://www.youtube.com/watch?v=iO85sohKwKg Learn more about Happiest Minds Ecommerce Solutions http://www.happiestminds.com/ecommerce-solutions/ Ecommerce Analytics http://www.happiestminds.com/ecommerce-analytics/ Retail Solutions http://www.happiestminds.com/industries-retail/ Website: http://www.happiestminds.com/ Have a question? Send us on: http://www.happiestminds.com/write%20to%20us Connect with us on: Facebook: https://www.facebook.com/happiestminds Twitter : http://twitter.com/#!/happiestminds LinkedIn : http://www.linkedin.com/company/happiest-minds-technologies Slideshare : http://www.slideshare.net/happiestminds Google + : https://plus.google.com/u/0/+happiestminds/posts
Views: 1204 Happiest Minds
Big Data Use Cases | Banking Data Analysis Using Hadoop | Big Data Case Study Part 1
 
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Big Data Use Cases: Banking Data Analysis Using Hadoop | Hadoop Tutorial Part 1 A leading banking and credit card services provider is trying to use Hadoop technologies to handle an analyse large amounts of data. Currently the organization has data in the RDBMS but wants to use the Hadoop ecosystem for storage, archival and analysis of large amounts of data. let’s get into the tutorial, Welcome to online Big Data training video conducted by Acadgild. This is the series of tutorial consists of real world Big Data use cases. In this project, you will be able to learn, • Understand the Project Requirement • What exactly the project is talking about • From where the data is coming • How the data is getting loaded into Hadoop, and • The different analysis that is performed with the Data Go through the entire video to understand the Big Data problems with finance departments and how to track the data. Enroll for big data and Hadoop developer training and certification to become successful Developer, https://acadgild.com/big-data/big-data-development-training-certification?utm_campaign=enrol-bigdata-usecase-part1-iQrao1C7juk_medium=VM&utm_source=youtube For more updates on courses and tips follow us on: Facebook: https://www.facebook.com/acadgild Twitter: https://twitter.com/acadgild LinkedIn: https://www.linkedin.com/company/acadgild
Views: 19448 ACADGILD
Data Mining for Ecommerce by Data Jacker
 
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http://goo.gl/jZRZoa . Data Jacker ... Mine Highly Lucrative Data for E-commerce & Affiliate Marketing with Data Jacker :)
Views: 2730 Ron R. Gat
Loggly Provides Scalable, Pay-as-you-go Logging Services Using AWS
 
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California-based Loggly provides logging as a service to help customers identify and resolve issues in real time. The company designed its service on AWS in order to provide customers with a pay-as-you-go model.
Views: 2070 Amazon Web Services
Data Integration for Oil & Gas Companies
 
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FME helps petroleum companies manage, import, export, transform, and validate high volumes of complex data. Hear from companies like Devon Energy, Colonial Pipeline, and Talisman Energy. For more information visit http://fme.ly/petroleum
Views: 402 FME Channel
sOnr Web Mining for Confluence - PoolParty Tutorial #23
 
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SONR IS A TOOL FOR MARKET OBSERVERS AND TREND SCOUTS (http://www.sonr-webmining.com/). With sOnr, you will keep track of everything that happens in a domain or industry of your interest. SONR IS BASED ON SEMANTIC TECHNOLOGIES. It is embedded in Atlassian Confluence, a highly useful collaboration platform. This architectural approach supports teams of market observers to extract relevant information from news services, blogs, and short messages automatically. SONR HELPS TO EXCHANGE IDEAS AND TO STRUCTURE KNOWLEDGE. A built-in semantic search engine is one of its core elements. Automatic agents crawl the web and the intranet. Collaborative features leverage the value of your findings! USERS WILL BENEFIT FROM - enterprise-readiness, - highly precise search results, - collaborative knowledge management, - a coffee break while sOnr is mining the web
'Small Business Web Pages' **Statistical Data Analysis**
 
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http://instantwebsitecreationtools.com/ 573-321-3462 small business web pages,make your own website,a web site,web design,website design,web site,small business,own website,how to,a website,web page,graphic design,free website,web,design,website
Views: 105 teampl01
Workshop: Visual Data Mining
 
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The Student Workshop "Visual Data Mining" had the goal to make the crosslinking between 2,000 companies from Forbes 2000 with 29,118 company relations visible. Theirby fokussing on: a) the extraction of relevant data, b) usable storing and structuring c) and interactive visualization of this data for the user The prototype was developed in java/processing. Participants of the workshop: Nikolay Borisov, Christian Brändel, Bettina Kirchner, Berit Lochner, Florian Schneider, Benjamin Vetter, Stefan Wagner Mentors: Marius Brade (Chair of Media Design), Klaus Engel (T-Systems Multimedia Solutions), Moritz Biehl (T-Systems Multimedia Solutions) and Rainer Groh (Chair of Media Design) Chair of Media Design, TU Dresden T-Systems Multimedia Solutions More information on: http://mg.inf.tu-dresden.de/lehre/ergebnisse/komplexpraktikum-visual-data-mining
Views: 590 MediaDesignTUD
What Is Big Data Analytics and How Does It Work
 
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Big data analytics is the examination of large sets of data – known as big data – to discover subtle correlations, hidden patterns, customer preferences, market trends, and a bevy of other valuable business information. The findings that big data analytics provides results in uncovering and creating more effective marketing strategies, increased revenue opportunities, competitive advantages, enhanced operational efficiency, improved customer service, and many more benefits to business. Big data can be drawn from many sources, including social media activity and content, Internet clickstream data, web server logs, texts, and emails. Data is analyzed by both people and statistical data analysis tools, such as data mining, predictive analytics, and text analytics. The information gleaned from this analysis helps companies shift from the traditional reactive nature of business – which is responding to feedback after the fact – to a proactive position where they can predict and respond to customer trends and preferences before it’s happened, putting massive amounts of collected data through customer analytics. While this obviously benefits businesses and consumers by creating improved operations, efficiency, and better tailoring to customer preferences, there is the uneasy drawback of the source of the data. Many consumers feel that there is no privacy in today’s world. Social networking platforms like Facebook sell their data while supermarkets and many other stores give away loyalty cards for the purpose of tracking purchase history and preferences. While this helps companies’ present customers with better suggestions and products, it leaves consumers feeling perpetually watched. With over a billion active users, Facebook is the world’s most ubiquitous site. Many people spend a great portion of their day using Facebook, so what does Facebook get in return for its social networking services? The answer is, quite a lot. Facebook, despite its lack of user fees, is a veritable goldmine for one of today’s most important resources – data. The users are Facebook’s source of wealth. With so much personal information stored in a user’s profile, pictures, and messages, Facebook is a major player in big data analytics.
Startup uses machine learning to identify programming errors with log analytics
 
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Coralogix applies machine learning to the analysis of software logs to find errors quickly. More than 70 percent of resolution time is wasted on discovering errors and bugs in corporate software, while only 30 percent is spent fixing them. The cost of this labor burden is a serious incentive for companies to seek out more advanced solutions. At Coralogix, we recognize that highly paid software engineers shouldn’t have to waste valuable time deciphering boatloads of unstructured string data (the standard format of software logs) when they could focus on creating products instead. They need a tool that will do the slogging for them—and do it right.
Introduction to Data Mining: Data Transformation
 
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In part seven of data preprocessing, we discuss transformation of data such as attribute transformation. -- At Data Science Dojo, we're extremely passionate about data science. Our in-person data science training has been attended by more than 3200+ employees from over 600 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Learn more about Data Science Dojo here: http://bit.ly/2mRDQ6C See what our past attendees are saying here: http://bit.ly/2nxiHwB -- Like Us: https://www.facebook.com/datascienced... Follow Us: https://plus.google.com/+Datasciencedojo Connect with Us: https://www.linkedin.com/company/data... Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_scienc... -- Vimeo: https://vimeo.com/datasciencedojo
Views: 4683 Data Science Dojo
Log Analysis with the ELK stack (Elasticsearch, Logstash, Kibana)
 
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It’s your first day at the new job and your new manager swings by your desk to tell you about your first assignment. You’re going to be in charge of log management and log analysis. Your job is to consolidate the log output to a central location from sources all around the company, such as, web servers, mail servers, firewalls, database servers, etc. But as a starting point you’re going to be consolidating, managing, and analyzing Syslog events. Suddenly, that job offer at cousin Rickey’s Ready Lube doesn’t look so bad. Instead of reaching for a grease gun, you reach for the ELK stack (Elasticsearch, Logstash, Kibana) The ELK stack makes searching and analyzing data easier than ever before. Using ELK you can gain insights in real-time from the log data from around the company. In this presentation, we’ll explore how you can consolidate the syslogs into a central store and delve into each of member of the ELK stack. Then we’ll put it them together to view and analyze log data. Finally, we’ll look at how the ELK can be used to do forensic analysis. Yes, there will be a demo.
Views: 18428 Jay Paul
Data Mining Full Bangla Tutorial 2017 || Data Entry Lesson- 4||
 
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Data Entry And Web Research Bangla Tutorial (2017) this tutorial i am going to teach you about data entry and web research.this is a tutorial for begginers data entry and web research have a great place in freelancing marketplaces.so after learning you guys can easily start doing this type of jobs ## Outsourcing Working Tips 2017 https://www.youtube.com/playlist?list=PLCTj6SR5wKSJqRnUVx7CSi1Cdc2KdD-F0 ## Data Entry Job A to Z Tutorial 2017 https://www.youtube.com/playlist?list=PLCTj6SR5wKSJNMpoVIxEcQLZscDRwkI3l ## Advance Internet Tricks https://www.youtube.com/playlist?list=PLCTj6SR5wKSJkKunzQUi8xTls2X5M9yZH ## Basic SEO Full Bangla Tutorial 2017 https://www.youtube.com/playlist?list=PLCTj6SR5wKSLjfUstoM8MDpc_MEvU24Ow ## SEO Full Bangla Tutorial 2017 https://www.youtube.com/playlist?list=PLCTj6SR5wKSKYTnjGvxvry98WhlyzecJb ## Basic To Advance Computer Operating And Internet Browsing Full Tutorial 2017 https://www.youtube.com/playlist?list=PLCTj6SR5wKSKbFCaphVP_Bij9JyOKz8-- In This Playlist 1. Simple Data Entry Job Full Bangla Tutorial 2017 || Data Entry Lesson- 1 https://youtu.be/9lhzyYRBJVg 2. Data Collection Full Bangla Tutorial (2017) || Data Entry Lesson- 2 https://youtu.be/eI2ktApDYew 3. BPO Data Entry Full Bangla Tutorial 2017 || Data Entry Lesson- 3 https://youtu.be/1nbtMVJpi38 4. Data Mining Full Bangla Tutorial 2017 || Data Entry Lesson- 4 https://youtu.be/P-WvkOMiLGA 5. Data Scraping Full Bangla Tutorial 2017 || Data Entry Lesson- 5 https://youtu.be/LpZ9XU1RogQ 6. Data Processing Full Bangla Tutorial 2017 || Data Entry Lesson- 6 7. Data Research Full Bangla Tutorial 2017 || Data Entry Lesson- 7 https://youtu.be/xCB4STWNTdg 8. Data Entry For Ecommerce Site Full Bangla Tutorial 2017 || Data Entry Lesson- 8 https://youtu.be/f8qb43o2wFA 9. Magento data entry Full Bangla Tutorial 2017 || Data Entry Lesson- 9 https://youtu.be/IWIB_GYqFYc 10. ERP Software Full Bangla Tutorial 2017 || Data Entry Lesson- 10 https://youtu.be/Wn3RpvElMFU 11. Data Convert Full Bangla Tutorial 2017 || Data Entry Lesson- 11 https://youtu.be/tYVjdwTOwGk #web research bangla tutorial #data entry bangla tutrorial #how to start doing data entry bangla tutorial #how to do data entry job bangla tutorial #Data Entry And Web Research Bangla Tutorial (2017) Data Entry And Web Research Bangla Tutorial ডাটা এন্টি জব, ডাটা এন্টি শিখবো, ডাটা এন্ট্রি বাংলা টিউটোরিয়াল,
Views: 1110 Silent Expo
Extract Facebook Data and save as CSV
 
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Extract data from the Facebook Graph API using the facepager tool. Much easier for those of us who struggle with API keys ;) . Blog Post: http://davidsherlock.co.uk/using-facepager-find-comments-facebook-page-posts/
Views: 184763 David Sherlock
MineExcellence - Drilling Data Analytics Platform
 
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The mobile and web-based platform enable a driller to add, view and edit each hole to record information for each layer or strata of the hole. The mobile version accepts information in offline mode and allows easy synchronization with online web version at a later time to produce real-time analytics and pattern visualization. Below are high-level features: Key aspects of the platform 1. Pre-Drill Activities: Assists in drilling administration work by removing the pen and paper system. By entering Pre-Drill information, it gives alerts related to maintenance and other issues, when the company is planning to mobilize a drilling operation with the same equipment beforehand to prevent unnecessary downtime. 2. Offline Capability – The mobile solution allows data capture against a drilling project in offline mode and later automatically synchronizes with online web version in an internet zone to produce reports & analytics and pattern visualization. 3. Eliminates the need for manual QA / QC – Automatic generation of periodic drilling operational analytics and reports based on the rate of penetration (ROP), Hole Deviation, time factor for different layers of strata and other machine data. 4. Operator Performance Analysis – Determines operator’s efficiency by analyzing idle time of drill and worker, the frequency of drill downtime etc. 5. Drill Bit performance analysis - Predicts drill bit breakdown and allows planned maintenance based on information from the measurable drilling parameters like pressure loss across a bit, rate of penetration (ROP), on bottom time, off bottom time etc. 6. On-site reports - The information captured in the drill log allows for auto-generation of drilling pattern report for on-site availability to drillers or blasters and a drill performance report to measure and analyze the difference between actual and planned drill. 7. Rock prediction - Empirical formulas are applied to the recorded data to predict the behavior of strata in terms of rock characteristics and mineral quality for e.g. Reference Data as shown below which is useful to determine the type of the lithology if basic MWD (Measurements while drilling tool is used), to get an idea of the formation on the spot by the driller and other personals before taking sample for detailed analysis.
Views: 514 Mine Excellence
Visual Data Analytics
 
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Fully customizable, real time, web based data analytics for your company.
Views: 874 ThinkLPI
Ecommerce Analytics - Click Stream Data Analytics
 
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Convert your abandoned shopping cart into sales. Identify segments and target your customers. Increase Conversion using click stream data analytics using predictive modelling techniques. Talk to us [email protected] Learn more about Happiest Minds Ecommerce Solution http://www.happiestminds.com/ecommerce-solutions/ Learn more about Happiest Minds Ecommerce Analytics http://www.happiestminds.com/ecommerce-analytics/ Related Links http://www.happiestminds.com/big-data-analytics/ Website http://www.happiestminds.com/ Have a question? Write to us http://www.happiestminds.com/write%20to%20us Connect with us on Facebook: https://www.facebook.com/happiestminds Twitter : http://twitter.com/#!/happiestminds LinkedIn : http://www.linkedin.com/company/happiest-minds-technologies Slideshare : http://www.slideshare.net/happiestminds Google + : https://plus.google.com/u/0/+happiestminds/posts
Views: 7795 Happiest Minds
Burstek LogAnalyzer 6 Install with ISA W3C Log Source
 
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Demonstrates how to install Burstek LogAnalyzer 6 into an ISA environment that is logging to W3C file types. Burstek's bt-LogAnalyzer 6 is Web log analysis software that offers comprehensive reporting in a concise, browser based format. As a core component of Burstek's Enterprise suite of products, bt-LogAnalyzer 6 provides the level of security insight and Internet log analysis necessary to make informed decisions about deployment, use and protection of a company's Internet and Email resources, and how to optimize these vital resources for maximum business benefit.
Views: 869 BurstTechInc
Web Mining Complete Introduction ( with Definition and it's type)
 
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CLICK TO GET COMPLETE COURSE :- https://gradesetter.com/ In this web data mining / web mining video i am going to discuss with you about data mining web or data mining websites with web content mining and web usage mining and also about web mining tools ?.data mining companies
text mining, web mining and sentiment analysis
 
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text mining, web mining
Views: 1402 Kakoli Bandyopadhyay
Introduction to Data Mining: Dimensionality Reduction
 
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In part five of data preprocessing, we discuss the curse of dimensionality and the purpose of dimensionality reduction. -- At Data Science Dojo, we're extremely passionate about data science. Our in-person data science training has been attended by more than 3200+ employees from over 600 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Learn more about Data Science Dojo here: http://bit.ly/2noCcpO See what our past attendees are saying here: http://bit.ly/2o9QK0c -- Like Us: https://www.facebook.com/datascienced... Follow Us: https://plus.google.com/+Datasciencedojo Connect with Us: https://www.linkedin.com/company/data... Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_scienc... -- Vimeo: https://vimeo.com/datasciencedojo
Views: 4033 Data Science Dojo
ANALYTICMATE  - DEMO TOUR - BIG DATA ANALYTICS
 
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Analyticmate is an analytical Big Data solution that offers to any company the possibility of gathering multiple data sources, structured or not, integrates and correlate them and get valuable business insights. Analyticmate offers three types of use cases: · Cybersecurity and compliance · Operational intelligence · Logs management and operations Analyticmate’s capabilities include: data ingestion, correlation, alerts and notifiers, compliance, dashboards, forensic and cybersecurity analysis. More information at www.analyticmate.com
Views: 885 Analytic mate
Vehicle Data Mining:  The Case for Data Analytics
 
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Transportation companies and companies operating vehicle fleets have access to an abundance of data related to their vehicles. Is your organization using this data effectively? For more information visit http://www.bkd.com.
Views: 171 BKD CPAs & Advisors
Hadoop Training with POC Projects @ BigDataTraining.IN
 
00:44
http://www.hadooptrainingchennai.in/contact/ http://www.bigdatatraining.in/hadoop-training-chennai/ http://www.bigdatatraining.in/machine-learning-training/ http://www.hadooptrainingchennai.in/bigdata-hadoop-projects/ http://www.bigdatatraining.in/hadoop-training-chennai/ Hadoop is an open-source software framework that supports data-intensive distributed applications, licensed under the Apache v2 license. It supports the running of applications on large clusters of commodity hardware. The Hadoop framework transparently provides both reliability and data motion to applications. The top three reasons mentioned for using Hadoop Mining data for improved Business Intelligence Reduces the cost of data analysis Log Analysis Apache Hadoop Training Chennai with Hands-On Practical Approach ! BigDataTraining.IN is a leading Global Talent Development Corporation, building skilled manpower pool for global industry requirements. BigData Training.in has today grown to be amongst world's leading talent development companies offering learning solutions to Individuals, Institutions & Corporate Clients. We assist more number of people with our student projects and provide exposure and support to the students with our Technical Architects every year. Lot of scholars from various colleges and universities are benefitted and hence, we still receive referrals from engineering colleges all over India. Hadoop Training Chennai with Hands-On Practical Approach ! Mail: [email protected] Call: +91 9789968765 044 - 42645495 Visit Us: #67, 2nd Floor, Gandhi Nagar 1st Main Road, Adyar, Chennai - 20 [Opp to Adyar Lifestyle Super Market]
Views: 23 sakthi v
Apache Hadoop Live Projects in India @ BigDataTraining.IN
 
00:16
http://www.hadooptrainingchennai.in/contact/ http://www.bigdatatraining.in/hadoop-training-chennai/ http://www.bigdatatraining.in/bigdata-consulting/big-data-services/ http://www.bigdatatraining.in/ Hadoop is an open-source software framework that supports data-intensive distributed applications, licensed under the Apache v2 license. It supports the running of applications on large clusters of commodity hardware. The Hadoop framework transparently provides both reliability and data motion to applications. The top three reasons mentioned for using Hadoop Mining data for improved Business Intelligence Reduces the cost of data analysis Log Analysis BigDataTraining.IN is a leading Global Talent Development Corporation, building skilled manpower pool for global industry requirements. BigData Training.in has today grown to be amongst world's leading talent development companies offering learning solutions to Individuals, Institutions & Corporate Clients. We assist more number of people with our student projects and provide exposure and support to the students with our Technical Architects every year. Lot of scholars from various colleges and universities are benefitted and hence, we still receive referrals from engineering colleges all over India. Contact us Mail: [email protected] Call: +91 9789968765 044 - 42645495 Visit Us: #67, 2nd Floor, Gandhi Nagar 1st Main Road, Adyar, Chennai - 20 [Opp to Adyar Lifestyle Super Market]
Views: 6 barathi vasan
Harnessing vehicle safety data with Watson Explorer Content Analytics
 
04:52
Discover how IBM Watson Explorer Content Analytics is helping safety analysts solve real-life problems by identifying previously unseen correlations within unstructured data. Thanks to Watson Explorer Content Analytics, manufacturers can take advantage of user feedback to help them address consumer safety issues at the point of failure. Subscribe to the IBM Analytics Channel: https://www.youtube.com/subscription_... The world is becoming smarter every day, join the conversation on the IBM Big Data & Analytics Hub: http://www.ibmbigdatahub.com https://www.youtube.com/user/ibmbigdata https://www.facebook.com/IBManalytics https://www.twitter.com/IBMAnalytics https://www.linkedin.com/company/ibm-... https://www.slideshare.net/IBMBDA
Views: 2533 IBM Analytics
Webinar: Event Processing & Data Analytics with Lucidworks Fusion (with Solr & Spark)
 
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Event processing is a common need in ecommerce systems to track business metrics such as views, conversions, cart analysis, click throughs, reviews, system logs, and more. However, there are many challenges faced in processing, analyzing, and using event streams to enhance these metrics. This webinar will take a look at how Lucidworks Fusion uses Solr and Spark to simplify event stream collection, aggregations at scale, and other data analytics tasks. You will learn: - How to capture & analyze user events - How to use signals for recommendations - Different types of recommendations that can be generated based on user type GitHub Link (Snowplow JS Tracker): https://github.com/snowplow/snowplow/wiki/javascript-tracker Lucidworks Solr Blog Posts: http://lucidworks.com/blog ________________________________________________________________________________________________________________________________________ Need advanced Solr capabilities now? Download Fusion: https://lucidworks.com/products/fusion/ Learn about Solr Training: https://lucidworks.com/resources/solr-training-and-consulting/ Contact Sales for a free Solr consultation: https://lucidworks.com/company/contact/ = = = Lucidworks powers search, analytics, and data discovery for some of the world’s largest brands. The Lucidworks Fusion platform enables developers to quickly build and deploy intelligent search-driven applications. Lucidworks is the commercial sponsor of the Apache Solr project and is the premiere provider of enterprise support and services for open source deployments. = = =
Views: 452 Lucidworks
Anomaly Detection: Algorithms, Explanations, Applications
 
01:26:56
Anomaly detection is important for data cleaning, cybersecurity, and robust AI systems. This talk will review recent work in our group on (a) benchmarking existing algorithms, (b) developing a theoretical understanding of their behavior, (c) explaining anomaly "alarms" to a data analyst, and (d) interactively re-ranking candidate anomalies in response to analyst feedback. Then the talk will describe two applications: (a) detecting and diagnosing sensor failures in weather networks and (b) open category detection in supervised learning. See more at https://www.microsoft.com/en-us/research/video/anomaly-detection-algorithms-explanations-applications/
Views: 5936 Microsoft Research
Final Year Projects 2015 | Automated web usage data mining and recommendation system
 
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Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/lGybbe Chat Now @ http://goo.gl/snglrO Visit Our Channel: http://www.youtube.com/clickmyproject Mail Us: [email protected]
Views: 518 ClickMyProject
Data Collection Full Bangla Tutorial (2017) || Data Entry Lesson- 2||
 
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Data Entry And Web Research Bangla Tutorial (2017) this tutorial i am going to teach you about data entry and web research.this is a tutorial for begginers data entry and web research have a great place in freelancing marketplaces.so after learning you guys can easily start doing this type of jobs ## Outsourcing Working Tips 2017 https://www.youtube.com/playlist?list=PLCTj6SR5wKSJqRnUVx7CSi1Cdc2KdD-F0 ## Data Entry Job A to Z Tutorial 2017 https://www.youtube.com/playlist?list=PLCTj6SR5wKSJNMpoVIxEcQLZscDRwkI3l ## Advance Internet Tricks https://www.youtube.com/playlist?list=PLCTj6SR5wKSJkKunzQUi8xTls2X5M9yZH ## Basic SEO Full Bangla Tutorial 2017 https://www.youtube.com/playlist?list=PLCTj6SR5wKSLjfUstoM8MDpc_MEvU24Ow ## SEO Full Bangla Tutorial 2017 https://www.youtube.com/playlist?list=PLCTj6SR5wKSKYTnjGvxvry98WhlyzecJb ## Basic To Advance Computer Operating And Internet Browsing Full Tutorial 2017 https://www.youtube.com/playlist?list=PLCTj6SR5wKSKbFCaphVP_Bij9JyOKz8-- In This Playlist 1. Simple Data Entry Job Full Bangla Tutorial 2017 || Data Entry Lesson- 1 https://youtu.be/9lhzyYRBJVg 2. Data Collection Full Bangla Tutorial (2017) || Data Entry Lesson- 2 https://youtu.be/eI2ktApDYew 3. BPO Data Entry Full Bangla Tutorial 2017 || Data Entry Lesson- 3 https://youtu.be/1nbtMVJpi38 4. Data Mining Full Bangla Tutorial 2017 || Data Entry Lesson- 4 https://youtu.be/P-WvkOMiLGA 5. Data Scraping Full Bangla Tutorial 2017 || Data Entry Lesson- 5 https://youtu.be/LpZ9XU1RogQ 6. Data Processing Full Bangla Tutorial 2017 || Data Entry Lesson- 6 7. Data Research Full Bangla Tutorial 2017 || Data Entry Lesson- 7 https://youtu.be/xCB4STWNTdg 8. Data Entry For Ecommerce Site Full Bangla Tutorial 2017 || Data Entry Lesson- 8 https://youtu.be/f8qb43o2wFA 9. Magento data entry Full Bangla Tutorial 2017 || Data Entry Lesson- 9 https://youtu.be/IWIB_GYqFYc 10. ERP Software Full Bangla Tutorial 2017 || Data Entry Lesson- 10 https://youtu.be/Wn3RpvElMFU 11. Data Convert Full Bangla Tutorial 2017 || Data Entry Lesson- 11 https://youtu.be/tYVjdwTOwGk #web research bangla tutorial #data entry bangla tutrorial #how to start doing data entry bangla tutorial #how to do data entry job bangla tutorial #Data Entry And Web Research Bangla Tutorial (2017) Data Entry And Web Research Bangla Tutorial
Views: 3681 Silent Expo
SmarterStats: Understanding your Web Analytic Software
 
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http://www.informaticsinc.com Your website plays a pivotal role in your company, so shouldn't you put it under the same analysis and scrutiny that you do with all elements of you business? Yes, you should, and to help you do that there are many web analytic software programs out there. If you website is hosted at Informatics, then you already have SmarterStats, a fantastic web analytic software package. Watch this video and you'll be on your way to getting the most out of your website. For more information, contact Informatics at http://www.informaticsinc.com
Views: 587 Informatics
DataSift: Allowing Enterprises to Benefit from Social Data Using Hadoop
 
02:49
As a Social Data Platform, DataSift helps companies analyze and mine business insights from social media data -- from public Tweets to Facebook posts, content on blogs, forums and message boards. DataSift is a real-time data processing platform that processes, aggregates, and filters data from billions of public social conversations in both real time and historically. DataSift's platform is powered by Cloudera Enterprise. In this video, DataSift founder & CTO Nick Halstead discusses their platform and partnership with Cloudera.
Views: 398 Cloudera, Inc.
IBM BigInsights on Cloud: Perform text analytics with BigInsights on Cloud
 
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This video shows you how to extract financial and other information from quarterly reports using Text Analytics in BigInsights on Cloud. Watch more videos in the BigInsights Learning Center at http://developer.ibm.com/clouddataservices/biginsights Get started with a BigInsights trial today! http://ibm.biz/biginsights-trial
Views: 749 IBM Cloudant
Building a data analytics engine on AWS, the Simple way
 
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Whether you are a smaller startup or a well-established company, data analytics can give you insights that drive engineering and business decisions. How can you build an engine like this, especially if you have limited resources? Once you do build the engine, how can you make sense of the data? These are two critical questions that Jeff Klukas answers for us in this episode. See how Simple built an engine on AWS with Redshift and learn from it. Scale and migrate large workloads after a free month test run on DigitalOcean, and get free Premier Support: https://scaleyourcode.com/digitalocean Already work on AWS and want to learn it inside and out? Get trained at your own convenience for $9 the first month: https://scaleyourcode.com/linuxacademy 1:22 - You were a research assistant for the University of Wisconsin in Madison. Can you tell us a little about what you did there? 4:00 - Now you're at Simple, which is a banking platform. Did you take that experience of automation and finding relationships with data and carried it to Simple? 5:19 - Simple is a banking platform. Can you tell us what it offers? 6:48 - Is that the kind of data that you're working with where you're crunching those numbers and trying to figure out what the "safe to spend" amount is and fraudulent activity and things like that, or are you working on a different set of data? 8:10 - You've built a funnel that receives data from different source and then you sort it out and use Redshift to make sense of that data. Can you walk us through how that's set up? How does Redshift receive data? Where does the data come from, etc? 10:34 - You have both internal and external facing APIs that receive data from different services you're using (like Postgres), as well as from other clients. After that, it goes to the loader which then batches it up and goes to Amazon S3 which then loads it into Redshift. Is that right? 11:05 - Did you build the loader itself? Is it custom built? 15:00 - Why Redshift instead of just leveraging PostgreSQL which you already have, or something like MySQL which a lot of people are really familiar with. What does Redshift have to offer that you can't find in those other engines? 18:08 - Redshift is still SQL based so you can still come from a background of MySQL or Postgres and still have the ability to quickly and accurately pull data. Are there any cons to that or is it all beneficial? 20:30 - Can you talk a little bit more about the distributive nature of Redshift and how it is able to distribute the data and how you know how it's distributing it so you can query more efficiently? 22:38 - Is it really trial and error when you're first getting started with Redshift if you don't have a lot of experience, or is it really understanding how that distributive nature works and then customizing the queries around that and then just trying and seeing which queries take a while and which queries need to be changed? Is that how you approached it? 24:42 - Redshift is actually an Amazon managed service, so are you able to easily plug it into CloudWatch and see some of those performance metrics or bottlenecks that you can quickly try to change or is that using other tools? 26:28 - I assume you can see those system tables in the Amazon Dashboard as well or you can use the API to pull that information and feed it into Grafana or whatever else you're using like that, right? 27:30 - Are you using the same monitoring tools to monitor things like RabbitMQ and Postgres and all those other services in your infrastructure? 28:19 - You also built a tool in Scala that collects and publishes Redshift performance metrics. Can you tell us a little bit more about that? 30:54 - Why Scala? The reason I'm asking this is because with Java 8 we've seen companies like LinkedIn where last I checked, they had moved to Scala and again, moved back to Java, I guess where they didn't see those benefits in performance or even finding the talent was difficult. Why are you using Scala? 33:30 - Do Java developers have a harder time switching to Scala because they use the Java way of doing things? 36:18 - We've been talking a lot about the back-end of this data analytics engine. At one point in time you have to visualize this data, right? How do you do that? 41:30 - How do you actually take the data from Redshift and plug it in to Periscope data? 43:10 - When you build realtime data analytics, how can you make sure that when an executive, engineer, customer, marketing agent or whoever looks at realtime data, that the data isn't skewed?
Views: 1496 Christophe Limpalair
Anomaly Detection in Telecommunications Using Complex Streaming Data | Whiteboard Walkthrough
 
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In this Whiteboard Walkthrough Ted Dunning, Chief Application Architect at MapR, explains in detail how to use streaming IoT sensor data from handsets and devices as well as cell tower data to detect strange anomalies. He takes us from best practices for data architecture, including the advantages of multi-master writes with MapR Streams, through analysis of the telecom data using clustering methods to discover normal and anomalous behaviors. For additional resources on anomaly detection and on streaming data: Download free pdf for the book Practical Machine Learning: A New Look at Anomaly Detection by Ted Dunning and Ellen Friedman https://www.mapr.com/practical-machine-learning-new-look-anomaly-detection Watch another of Ted’s Whiteboard Walkthrough videos “Key Requirements for Streaming Platforms: A Microservices Advantage” https://www.mapr.com/blog/key-requirements-streaming-platforms-micro-services-advantage-whiteboard-walkthrough-part-1 Read technical blog/tutorial “Getting Started with MapR Streams” sample programs by Tugdual Grall https://www.mapr.com/blog/getting-started-sample-programs-mapr-streams Download free pdf for the book Introduction to Apache Flink by Ellen Friedman and Ted Dunning https://www.mapr.com/introduction-to-apache-flink
Views: 4139 MapR Technologies
Apache Spark with Scala :  Learn Spark from a Big Data Guru | BEST SELLER
 
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This course covers all the fundamentals about Apache Spark with Scala and teaches you everything you need to know about developing Apache Spark applications with Scala Spark. At the end of this course, you will gain in-depth knowledge about Apache Spark Scala and general big data analysis and manipulations skills to help your company to adapt Apache Scala Spark for building big data processing pipeline and data analytics applications. This course covers 10+ hands-on big data examples involving Apache Spark. You will learn valuable knowledge about how to frame data analysis problems as Scala Spark problems. Together we will learn examples such as aggregating NASA Apache web logs from different sources; we will explore the price trend by looking at the real estate data in California; we will write Scala Spark applications to find out the median salary of developers in different countries through the Stack Overflow survey data; we will develop a system to analyze how maker spaces are distributed across different regions in the United Kingdom. And much much more. What will you learn from this lecture: In particularly, you will learn: An overview of the architecture of Apache Spark. Develop Apache Spark 2.0 applications with Scala using RDD transformations and actions and Spark SQL. Work with Apache Spark's primary abstraction, resilient distributed datasets(RDDs) to process and analyze large data sets. Deep dive into advanced techniques to optimize and tune Apache Spark jobs by partitioning, caching and persisting RDDs. Scale up Apache Spark applications on a Hadoop YARN cluster through Amazon's Elastic MapReduce service. Analyze structured and semi-structured data using Datasets and DataFrames, and develop a thorough understanding of Apache Spark SQL. Share information across different nodes on an Apache Spark cluster by broadcast variables and accumulators. Best practices of working with Apache Spark Scala in the field. Big data ecosystem overview. Why shall we learn Apache Spark: Apache Spark gives us unlimited ability to build cutting-edge applications. It is also one of the most compelling technologies of the last decade in terms of its disruption to the big data world. Apache Scala Spark provides in-memory cluster computing which greatly boosts the speed of iterative algorithms and interactive data mining tasks. Apache Spark is the next-generation processing engine for big data. Tons of companies are adapting Apache Spark to extract meaning from massive data sets, today you have access to that same big data technology right on your desktop. Apache Spark is becoming a must tool for big data engineers and data scientists. What programing language is this course taught in? This course is taught in Scala. Scala is the next generation programming language for functional programing that is growing in popularity and it is one of the most widely used languages in the industry to write Apache Spark programs. Let's learn how to write Apache Spark programs with Scala to model big data problem today! 30-day Money-back Guarantee! You will get 30-day money-back guarantee from Udemy for this course. If not satisfied with Apache Spark course, simply ask for a refund within 30 days. You will get a full refund. No questions whatsoever asked. Are you ready to take your big data analysis skills and career to the next level, take this course now! You will go from zero to Apache Spark hero in 4 hours. Course Link : http://bit.ly/2DKjsZD Google Searching Text: spark with scala tutorial,scala for spark pdf,apache spark tutorial,spark with scala book,spark scala example,spark scala wiki,spark tutorials with scala the beginner's guide pdf,what is spark,
SensePlace2: Visual Analytics and Big Data for Spatiotemporal Sensemaking
 
03:01
This video demonstrates SensePlace2, a geovisual analytics application developed within the GeoVISTA Center at The Pennsylvania State University, SensePlace2 leverages a web-based visual analytics stack to allow analysts to query tweets that contain place and topic mentions. Each place mention is mapped so that the connections between and across places, events, and times can be interactively explored by the user. For more information, please visit http://www.geovista.psu.edu/SensePlace2 SensePlace2: Visual Analytics and Big Data for Spatiotemporal Sensemaking by Joshua E. Stevens is licensed under a Creative Commons Attribution-NoDerivs 3.0 Unported License. Please cite as: Joshua E. Stevens, 2013. SensePlace2: Visual Analytics and Big Data for Spatiotemporal Sensemaking, Video Posted on Youtube, April 30, 2013.
Views: 2864 Joshua Stevens
Hongjoo Lee - Deep Learning your Broadband Network @HOME
 
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"Deep Learning your Broadband Network @HOME [EuroPython 2017 - Talk - 2017-07-14 - Anfiteatro 1] [Rimini, Italy] Most of us have broadband internet services at home. Sometimes it does not work well, and we visit speed test page and check internet speed for ourselves or call cable company to report the service failure. As a Python programmer, have you ever tried to automate the internet speed test on a regular basis? Have you ever thought about logging the data and analyzing the time series ? In this talk, we will go through the whole process of data mining and knowledge discovery. Firstly we write a script to run speed test periodically and log the metric. Then we parse the log data and convert them into a time series and visualize the data for a certain period. Next we conduct some data analysis; finding trends, forecasting, and detecting anomalous data. There will be several statistic or deep learning techniques used for the analysis; ARIMA (Autoregressive Integrated Moving Average), LSTM (Long Short Term Memory). The goal is to provide basic idea how to run speed test and collect metrics by automated script in Python. Also, I will provide high level concept of the methodologies for analyzing time series data. Also, I would like to motivate Python people to try this at home. This session is designed to be accessible to everyone, including anyone with no expertise in mathematics, computer science. Understandings of basic concepts of machine learning and some Python tools bringing such concepts into practice might be helpful, but not necessary for the audience. License: This video is licensed under the CC BY-NC-SA 3.0 license: https://creativecommons.org/licenses/by-nc-sa/3.0/ Please see our speaker release agreement for details: https://ep2017.europython.eu/en/speaker-release-agreement/
RubyConf 2017: Using Ruby in data science by Kenta Murata
 
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Using Ruby in data science by Kenta Murata I will talk about the current situation and the future of Ruby in the field of data science. Currently, Ruby can be used practically in data science. In the first half of this talk, I will perform some demonstrations to prove this. You will see that pandas, matplotlib, scikit-learn, and several deep learning frameworks are available from Ruby scripts in these demos. In the future, in order for Ruby to continue to be used in data science, we need to continue some efforts. In the latter half of this talk, we will introduce Red Data Tools project that plays an important role in this context.
Views: 564 Confreaks
Incident Handling and Log Analysis for Web Based - Part 1 - ClubHack 2009
 
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ClubHack 2009 Hacking and Security Conference Speaker: Manindar Kishore
Views: 112 ClubHackTv
DEF CON 16 - Workshop: Davix Workshop
 
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Workshop: Davix Workshop Need help understanding your gigabytes of application logs or network captures? Your OS performance metrics do not make sense? Then DAVIX, the live CD for visualizing IT data, is your answer! To simplify the analysis of vast amounts of security data, visualization is slowly penetrating the security community. There are many free tools available for analysis and visualization of data. To simplify the use of these tools, the open source project DAVIX was put to life and is released this year at BlackHat/DEFCON. At this "Bring Your Own Laptop" workshop we will introduce you to DAVIX. The workshop starts with an introduction to the set of available tools, the integrated manual, as well as customizing the CD to your needs. In a second part, you can use DAVIX to analyze a set of provided packet captures. In the end we will show some of the visualizations created by the participants. Be prepared for pretty and meaningful pictures! For you to be able to participate in the analysis part of the workshop, you should bring an Intel or AMD x86 based notebook with at least 1GB of memory and a wireless LAN adapter. To avoid problems with the Wireless card setup we strongly recommend that you run DAVIX in VMware Player or VMware Fusion in NAT mode. The DAVIX ISO image should be downloaded before the workshop from the davix.secviz.org homepage. The network capture files will be made available during the workshop. Jan P. Monsch is senior security analyst with the leading Swiss security assessment company Compass Security AG. He has almost 10 years experience in the field of IT security and most of it in the Swiss banking and insurance industry. His talent in understanding and assessing security in large environments has got him involved in several outsourcing projects with international participation. Apart from reviewing security he has trained many software developers, IT engineers and security officers in the fields of application and content security. His passion for application security and interest for better understanding security in real-world applications has lead him to the field of security visualization. The lack of broadly available solutions for data analysis and security visualization has motivated him to create DAVIX - The Data Analysis &Visualization Linux. Raffael Marty: As chief security strategist and senior product manager, Raffy is customer advocate and guardian - expert on all things security and log analysis at Splunk. With customers, he uses his skills in data visualization, log management, intrusion detection, and compliance to solve problems and create solutions. Inside Splunk, he is the conduit for customer issues, new ideas and market requirements to the development team. Fully immersed in industry initiatives, standards efforts and activities, Raffy lives and breathes security and visualization. His passion for visualization is evident in the many presentations he gives at conferences around the world and the upcoming "Applied Security Visualization" book. In addition, Raffy is the author of AfterGlow, founder of the security visualization portal https://secviz.org, and contributing author to a number of books on security and visualization. For copies of the slides and additional materials please see the DEF CON 16 Archive here: https://defcon.org/html/links/dc-archives/dc-16-archive.html
Views: 722 DEFCONConference
Big Data - Step by Step - How To Get Started
 
44:11
You've likely heard a lot of talk about Big Data. Corporations are dealing with data sets so large and complex that traditional methods of analyzing the information cannot deliver the insight needed to profit and compete. Smart companies are using Big Data solutions to process data more efficiently, with more detail than ever before. Analysts say Big Data is not just a trend, but a corporate turning point that business leaders need to plan for now. During this webinar, we will provide a step-by-step approach to getting started with a Big Data solution and what to expect in the first 90 days including: • 10 Steps to Starting your Big Data Project • 5 Critical Mistakes • 2 Practical Success Stories Join us to find out how Big Data can give your company a competitive advantage, new operational efficiencies and new revenue streams.
Views: 5504 Pactera US
Facebook CEO Mark Zuckerberg testifies before Congress on data scandal
 
04:52:51
Facebook CEO Mark Zuckerberg will testify today before a U.S. congressional hearing about the use of Facebook data to target voters in the 2016 election. Zuckerberg is expected to offer a public apology after revelations that Cambridge Analytica, a data-mining firm affiliated with Donald Trump's presidential campaign, gathered personal information about 87 million users to try to influence elections. »»» Subscribe to CBC News to watch more videos: http://bit.ly/1RreYWS Connect with CBC News Online: For breaking news, video, audio and in-depth coverage: http://bit.ly/1Z0m6iX Find CBC News on Facebook: http://bit.ly/1WjG36m Follow CBC News on Twitter: http://bit.ly/1sA5P9H For breaking news on Twitter: http://bit.ly/1WjDyks Follow CBC News on Instagram: http://bit.ly/1Z0iE7O Download the CBC News app for iOS: http://apple.co/25mpsUz Download the CBC News app for Android: http://bit.ly/1XxuozZ »»»»»»»»»»»»»»»»»» For more than 75 years, CBC News has been the source Canadians turn to, to keep them informed about their communities, their country and their world. Through regional and national programming on multiple platforms, including CBC Television, CBC News Network, CBC Radio, CBCNews.ca, mobile and on-demand, CBC News and its internationally recognized team of award-winning journalists deliver the breaking stories, the issues, the analyses and the personalities that matter to Canadians.
Views: 125766 CBC News