Introduction to Machine Learning with ENCOG 3

This course is focused on implementation and applications of various machine learning methods.
Course info
Rating
(483)
Level
Intermediate
Updated
Jul 22, 2013
Duration
2h 19m
Table of contents
Introduction to Machine Learning
Applications of Machine Learning
Machine Learning Tasks
Introduction to Neural Networks
Introduction to ENCOG 3
Neural Network Components in ENCOG for .NET
Propagation Training
Data Normalization
Case Studies (Classification and Regression Task)
Description
Course info
Rating
(483)
Level
Intermediate
Updated
Jul 22, 2013
Duration
2h 19m
Description

This course is focused on implementation and applications of various machine learning methods. As machine learning is a very vast area, this course will be targeted more towards one of the machine learning methods which is neural networks. The course will try to make a base foundation first by explaining machine learning through some real world applications and various associated components. In this course, we'll take one of the open source machine learning framework for .NET, which is ENCOG. The course will explain how ENCOG fits into the picture for machine learning programming. Then we'll learn to create various neural network components using ENCOG and how to combine these components for real world scenarios. We'll go in detail of feed forward networks and various propagation training methodologies supported in ENCOG. We'll also talk about data preparation for neural networks using normalization process. Finally, we will take a few more case studies and will try to implement tasks of classification & regression. In the course I will also give some tips & tricks for effective & quick implementations of neural networks in real world applications.

About the author
About the author

Abhishek Kumar is a data science consultant, author and speaker.He holds Master’s degree from University of California, Berkeley.His focus area is machine learning & deep learning at scale.

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