Have you been thinking about getting up to speed with deep learning or applied data ethics? Well, look no further than the latest free courses from fast.ai.
Fast.ai recently announced some exciting new releases. Here is their full list of available courses:
This course covers the following topics:
Part 2 of the deep learning course shows how to build a state of the art deep learning model from scratch. It covers many topics from the foundations of implementing matrix multiplication and back-propagation, through to high performance mixed-precision training, and the latest neural network architectures and learning techniques.
This course focusses on ethics issues that are both urgent and practical. It covers the following topics:
In this course you can learn how to do matrix computations with acceptable speed and acceptable accuracy.
This course teaches a blend of traditional NLP topics (including regex, SVD, naive bayes, tokenization) and recent neural network approaches (including RNNs, seq2seq, attention, and the transformer architecture). It also addresses urgent ethical issues, such as bias and disinformation.
fast.ai is a self-funded research, software development, and teaching lab, focused on making deep learning more accessible. It was founded by Jeremy Howard and Rachel Thomas in 2016, with Sylvain Gugger completing the core team. They provide free courses, software libraries and research papers (with no ads), and pay all of the costs out of their own pockets. Jeremy and Sylvain have recently published a book entitled: “Deep Learning for Coders with fastai and PyTorch: AI Applications Without a PhD”.