Machine Learning

Practical Deep Learning for Coders (Review)

Last Updated on November 1, 2019

Practical deep learning is a challenging subject in which to get started.

It is often taught in a bottom-up manner, requiring that you first get familiar with linear algebra, calculus, and mathematical optimization before eventually learning the neural network techniques. This can take years, and most of the background theory will not help you to get good results, fast.

Instead, a top-down approach can be used where first you learn how to get results with deep learning models on real-world problems and later learn more about how the methods work.

This is the exact approach used in the popular cause taught at fast.ai titled “Practical Deep Learning for Coders.”

In this post, you will discover the fast.ai course for developers looking to get started and get good at deep learning, including an overview of the course itself, the best practices introduced in the course, and a discussion and review of the whole course.

Kick-start your project with my new book Deep Learning With Python, including step-by-step tutorials and the Python source code files for all examples.

Let’s get started.