Several design patterns are discussed with practical examples and their implications. So not only you want to build neural networks and other machine learning algorithms, but also you want to find the best hyperparameters for them automatically. We’ll here demonstrate how it’s possible in a clean code way.
Applying clean code and SOLID principles to your ML projects is crucial, and is so often overlooked. Successful artificial intelligence projects require good programmers to work in pair with the mathematicians.
Ugly research code simply won’t do it. You need to do Clean Machine Learning at the moment you begin your project.
Despite all the hype being about the deep learning algorithms, we decided at Neuraxio to do a training about Clean Machine Learning, because it is was we feel the industry really needs.
Clean code is excessively hard to achieve in a codebase that is already dirty, action truly must be taken at the beginning of the project. It must not be postponed.