Advanced Neural Networks in R - A Practical Approach

Neural networks are powerful predictive tools that can be used for almost any machine learning problem with very good results. If you want to break into deep learning and artificial intelligence, learning neural networks is the first crucial step. This is why I'm inviting you to an exciting journey through the world of complex, state-of-the-art neural networks.

In this course you will develop a strong understanding of the most utilized neural networks, suitable for both classification and regression problems. The mathematics behind neural networks is particularly complex, but you don't need to be a mathematician to take this course and fully benefit from it. We will not dive into complicated maths - our emphasis here is on practice.

You will learn how to operate neural networks using the R program, how to build and train models and how to make predictions on new data. All the procedures are explained live, on real life data sets. So you will advance fast and be able to apply your knowledge immediately.

This course contains four comprehensive sections. 1. Multilayer Perceptrons - Beyond the BasicsLearn to use multilayer perceptrons to make predictions for both categorical and continuous variables.