About the module

In this module you'll jump into deep water, applying modern deep learning techniques without necessarily knowing what's going on under the hood (that'll come later!).

Todos

The module assumes that you've set up your computer or gotten access to and become comfortable with a suitable cloud infrastructure, as described in Welcome to DAT255!
The most important thing you'll do in this module is to watch Lesson 1 of course.fast.ai and the first 1:14:00 of Lesson 2 of course.fast.ai, as well as work through the corresponding notebook found in the fastbook repo https://github.com/fastai/fastbook, i.e. https://github.com/fastai/fastbook/blob/master/clean/01_intro.ipynb.
NB: Don't just watch the videos: make sure to spend a lot of time working with the accompanying notebooks.
Think about possible course mini-projects and/or sign up for one of the proposed projects, as described in Mini-projects [TBA]. You should start thinking about and proposing such mini-projects from the beginning of this module, and throughout the rest of the course.

Additional sources

You should read through the preface, the foreword and chapter 1 of the textbook. If you have the actual book either on paper or electronically, that's great, but also remember that it's available for free online: https://github.com/fastai/fastbook.
The first chapter of François Chollet's book Deep Learning with Python, Second Edition is a great supplementary companion to this module. You can read it for free here: https://livebook.manning.com/book/deep-learning-with-python-second-edition/chapter-1. (Chollet is the creator of the Keras deep learning library, now tightly integrated with TensorFlow. We'll learn much more about TensorFlow and Keras later in the course).