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.