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Intro to Neural Networks and Machine Learning
1
Instructor: Roger Grosse
Department: Computer Science
Institution: University of Toronto
Platform: Independent
Year: 2017
Price: Free
Description:
Machine learning is a powerful set of techniques that allow computers to learn from data rather than having a human expert program a behavior by hand. Neural networks are a class of machine learning algorithm originally inspired by the brain, but which have recently have seen a lot of success at practical applications. They're at the heart of production systems at companies like Google and Facebook for face recognition, speech-to-text, and language understanding. This course gives an overview of both the foundational ideas and the recent advances in neural net algorithms. Roughly the first 2/3 of the course focuses on supervised learning -- training the network to produce a specified behavior when one has lots of labeled examples of that behavior. The last 1/3 focuses on unsupervised learning -- the algorithm isn't given any examples of the correct behavior, and the goal is instead to discover interesting regularities in the data.