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Videos uploaded by user “Derek Kane”
Data Science - Part XII - Ridge Regression, LASSO, and Elastic Nets
 
01:04:53
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview of some modern regression techniques including a discussion of the bias variance tradeoff for regression errors and the topic of shrinkage estimators. This leads into an overview of ridge regression, LASSO, and elastic nets. These topics will be discussed in detail and we will go through the calibration/diagnostics and then conclude with a practical example highlighting the techniques.
Views: 67645 Derek Kane
Data Science - Part IX -  Support Vector Machine
 
31:14
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview of Support Vector Machines in a more relatable and accessible manner. We will go through some methods of calibration and diagnostics of SVM and then apply the technique to accurately detect breast cancer within a dataset.
Views: 10550 Derek Kane
Data Science - Part VI - Market Basket and Product Recommendation Engines
 
40:04
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview of association analysis, which includes topics such as market basket analysis and product recommendation engines. The first practical example centers around analyzing supermarket retailer product receipts and the second example touches upon the use of the association rules in the political arena.
Views: 30134 Derek Kane
Data Science - Part III -  EDA & Model Selection
 
01:48:37
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture introduces the concept of EDA, understanding, and working with data for machine learning and predictive analysis. The lecture is designed for anyone who wants to understand how to work with data and does not get into the mathematics. We will discuss how to utilize summary statistics, diagnostic plots, data transformations, variable selection techniques including principal component analysis, and finally get into the concept of model selection.
Views: 34525 Derek Kane
Data Science - Part X - Time Series Forecasting
 
01:25:59
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview of Time Series forecasting techniques and the process of creating effective forecasts. We will go through some of the popular statistical methods including time series decomposition, exponential smoothing, Holt-Winters, ARIMA, and GLM Models. These topics will be discussed in detail and we will go through the calibration and diagnostics effective time series models on a number of diverse datasets.
Views: 57147 Derek Kane
Data Science - Part I - Building Predictive Analytics Capabilities
 
01:52:19
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This is the first video lecture in a series of data analytics topics and geared to individuals and business professionals who have no understand of building modern analytics approaches. This lecture provides an overview of the models and techniques we will address throughout the lecture series, we will discuss Business Intelligence topics, predictive analytics, and big data technologies. Finally, we will walk through a simple yet effective example which showcases the potential of predictive analytics in a business context.
Views: 158290 Derek Kane
Data Science - Part XIII - Hidden Markov Models
 
01:08:22
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview on Markov processes and Hidden Markov Models. We will start off by going through a basic conceptual example and then explore the types of problems that can be solved with HMM's. The underlying algorithms will be discussed in detail with a quantitative focus and then we will conclude with a practical example concerning stock market prediction which highlights the techniques.
Views: 45813 Derek Kane
Data Science - Part IV - Regression Analysis and ANOVA Concepts
 
01:32:31
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview of linear regression analysis, interaction terms, ANOVA, optimization, log-level, and log-log transformations. The first practical example centers around the Boston housing market where the second example dives into business applications of regression analysis in a supermarket retailer.
Views: 35646 Derek Kane
Data Science - Part XV - MARS, Logistic Regression, & Survival Analysis
 
01:22:43
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview on extending the regression concepts brought forth in previous lectures. We will start off by going through a broad overview of the Multivariate Adaptive Regression Splines Algorithm, Logistic Regression, and then explore the Survival Analysis. The presentation will culminate with a real world example from my consulting work on how these techniques can be used in the US criminal justice system.
Views: 11794 Derek Kane
Data Science - Part XIV - Genetic Algorithms
 
01:33:50
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview on biological evolution and genetic algorithms in a machine learning context. We will start off by going through a broad overview of the biological evolutionary process and then explore how genetic algorithms can be developed that mimic these processes. We will dive into the types of problems that can be solved with genetic algorithms and then we will conclude with a series of practical examples in R which highlights the techniques: The Knapsack Problem, Feature Selection and OLS regression, and constrained optimizations.
Views: 21346 Derek Kane
Data Science - Part XVI - Fourier Analysis
 
43:39
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview of the Fourier Analysis and the Fourier Transform as applied in Machine Learning. We will go through some methods of calibration and diagnostics and then apply the technique on a time series prediction of Manufacturing Order Volumes utilizing Fourier Analysis and Neural Networks.
Views: 9947 Derek Kane
Data Science - Part XVII - Deep Learning & Image Processing
 
02:08:50
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview of Image Processing and Deep Learning for the applications of data science and machine learning. We will go through examples of image processing techniques using a couple of different R packages. Afterwards, we will shift our focus and dive into the topics of Deep Neural Networks and Deep Learning. We will discuss topics including Deep Boltzmann Machines, Deep Belief Networks, & Convolutional Neural Networks and finish the presentation with a practical exercise in hand writing recognition techniques on the MNIST dataset.
Views: 15849 Derek Kane
Data Science - Part II -  Working with R & R Studio
 
57:30
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This tutorial will go through a basic primer for individuals who want to get started with predictive analytics through downloading the open source (FREE) language R. I will go through some tips to get up and started and building predictive models ASAP.
Views: 33352 Derek Kane
Data Science - Part XI - Text Analytics
 
01:57:28
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This is an introduction to text analytics for advanced business users and IT professionals with limited programming expertise. The presentation will go through different areas of text analytics as well as provide some real work examples that help to make the subject matter a little more relatable. We will cover topics like search engine building, categorization (supervised and unsupervised), clustering, NLP, and social media analysis.
Views: 16227 Derek Kane
Data Science - Part V -  Decision Trees & Random Forests
 
51:07
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview of decision tree machine learning algorithms and random forest ensemble techniques. The practical example includes diagnosing Type II diabetes and evaluating customer churn in the telecommunication industry.
Views: 66624 Derek Kane
Data Science - Part VIII -  Artifical Neural Network
 
50:04
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview of biological based learning in the brain and how to simulate this approach through the use of feed-forward artificial neural networks with back propagation. We will go through some methods of calibration and diagnostics and then apply the technique on three different data mining tasks: binary prediction, classification, and time series prediction.
Views: 12191 Derek Kane
Data Science - Part VII -  Cluster Analysis
 
36:45
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview of clustering techniques, including K-Means, Hierarchical Clustering, and Gaussian Mixed Models. We will go through some methods of calibration and diagnostics and then apply the technique on a recognizable dataset.
Views: 16895 Derek Kane
Data Science - Part XVIII - Big Data Fundamentals for Data Scientists
 
02:53:49
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture will focus our attention towards understanding the Big Data landscape from a Data Scientists perspective. The presentation will start off with a brief overview of the need for large scale data processing technologies and then introduce the underlying technologies which drive the modern big data landscape. The techniques pioneered by the Apache Foundation will be discussed in some technical detail, however, the emphasis will remain on creating a broad awareness of the Hadoop 2.0technologies as it relates to data science and machine learning. We will then introduce some mechanisms for applying the MapReduce framework, accessing HDFS data, and creating analytics within the R programming language. Finally, we will bring all of the Big Data concepts into focus through working a practical example of New York Taxi Cab data within R.
Views: 10857 Derek Kane