Fast.ai - Part 1 - Lesson 1 - Annotated notes

[Update April 15, 2019] This blog post covers the 2018 course which you can find here. TL;DR The first lesson gives an introduction into the why and how of the fast.ai course, and you will learn the basics of Jupyter Notebooks and how to use the fast.ai library to build a world-class image classifier in three lines of Python. You will get a feel for what deep learning is and why it works, as well as possible applications you can build yourself.

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Fast.ai: Up to speed with the best of Deep Learning

[Update April 15, 2019] This blog post covers the 2018 course which you can find here. (Copyright fast.ai) Most approaches teaching machine and deep learning can be cumbersome and time-consuming: Stepping through all the details of (basic) linear algebra, activation functions and slowly building a neural network, so that after a few weeks/months, you are able to build an image classifier, if you have actually powered through… Do not get me wrong, understanding the intuition and fundamentals of linear algebra and neural networks are an important and invaluable asset in achieving great results.

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