Introduction to Machine Learning with ENCOG 3

This machine-learning course is focused on implementation and applications of various machine learning methods with ENCOG 33. Start your free trial today!

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.

• Introduction to Machine Learning 5mins
• Applications of Machine Learning 7mins
• Machine Learning Tasks 12mins
• Introduction to Neural Networks 23mins
• Introduction to ENCOG 3 5mins
• Neural Network Components in ENCOG for .NET 17mins
• Propagation Training 14mins
• Data Normalization 15mins
• Case Studies (Classification and Regression Task) 37mins