Deep Learning Optimisation Techniques

About This Course

Deep learning neural networks are generally easy to define and fit, however, they are still hard to configure for optimum performance. There are no hard and fast rules to optimise a network for a given problem and we cannot analytically calculate the optimal model type or model configuration for a given dataset. In this course, participants will work through techniques that improve model learning in response to a training dataset, reduced overfitting and improve prediction.

We recommend participants completed Deep Learning with Python before signing up for this course.
Lesson 1: Framework for deep learning optimization
Lesson 2: Techniques for optimising learning
Lesson 3: Techniques for optimizing generalisation
Lesson 4: Techniques for improving prediction