Deep learning is a type of machine learning that uses artificial neural networks with multiple layers. It has been successfully applied to various fields and can produce results comparable to or better than human experts. Artificial neural networks differ from biological brains in their static and symbolic nature, while deep learning allows for heterogeneous layers that are not biologically inspired.
Stanford University
Fall 2022
An in-depth course focused on building neural networks and leading successful machine learning projects. It covers Convolutional Networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. Students are expected to have basic computer science skills, probability theory knowledge, and linear algebra familiarity.
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+ 35 more conceptsStanford University
Fall 2022
Focused on principles and trade-offs in designing modern parallel computing systems, this course also teaches parallel programming techniques. It is intended for students looking to understand both parallel hardware and software design. Prerequisite knowledge in computer systems is required.
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+ 45 more concepts