Advanced Machine Learning with ENCOG - Part 2
Pluralsight
Course Summary
In this course, you will learn to implement dimensionality reduction and clustering using self-organizing maps, pattern recall and reconstruction using Hopfield networks, time series forecasting using temporal dataset, and optimization using genetic algorithm. This course will not only provide you fundamental knowledge of aforementioned topics, but also will help you to implement these applications using ENCOG machine learning framework.
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Course Description
Finding patterns in a multidimensional dataset has always been a challenging task, but self-organizing maps can simplify this process and can help to find interesting patterns and inferences. In this course, you will learn not only the fundamentals of self-organizing maps but also the implementation in a C# application using the ENCOG machine learning framework. In this course, you will also learn to use Hopfield networks in a pattern recall and reconstruction application. This course will also provide a real world case study on time series forecasting, where you will learn to forecast future behavior using historical values. The course also covers another very important aspect of machine learning: optimization. You will learn to solve optimization problems with the help of genetic algorithms. The concepts learned in this course are applicable for developers working in any other framework in any other language.
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Course Syllabus
Course Introduction- 6m 1s
—Introduction 2m 10s
—Course Scope 2m 46s
—Course Structure 1m 4sUnsupervised Competitive Networks- 1h 11m
—Introduction 1m 4s
—Outline 1m 10s
—Unsupervised Learning 2m 59s
—Unsupervised Learning Tasks 6m 0s
—Unsupervised Networks 2m 4s
—Self-Organizing Map (SOM) Introduction 2m 6s
—Example Dataset 1m 21s
—SOM Network Topology 3m 54s
—SOM Training 7m 35s
—SOM Training Using ENCOG 6m 15s
—SOM Demo: Setup SOM Network (XAML Part) 5m 13s
—SOM Demo: Setup SOM Network (Code Behind) 10m 18s
—SOM Demo: Training SOM Network 3m 47s
—SOM Demo: Overlay 5m 12s
—SOM Demo: Alternative Visualization Approach 8m 24s
—Applications of SOM 2m 10s
—Other Unsupervised Learning Techniques 0m 50s
—Summary 1m 18sUnsupervised Auto-Associative Networks- 27m 31sCase Study: Time Series Forecasting- 45m 1sOptimization Using Genetic Algorithm- 1h 5mCourse Summary- 6m 20s
