Applied Deep Learning in Python Mini-Course

Last Updated on December 11, 2019

Deep learning is a fascinating field of study and the techniques are achieving world class results in a range of challenging machine learning problems.

It can be hard to get started in deep learning.

Which library should you use and which techniques should you focus on?

In this post you will discover a 14-part crash course into deep learning in Python with the easy to use and powerful Keras library.

This mini-course is intended for python machine learning practitioners that are already comfortable with scikit-learn on the SciPy ecosystem for machine learning.

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.

(Tip: you might want to print or bookmark this page so that you can refer back to it later.)

• Update Mar/2018: Added alternate link to download the dataset as the original appears to have been taken down.
• Update Oct/2019: Updated for Keras 2.3.0.