Here're some machine learning and computational modeling resources for researchers in psychology and neuroscience.
Online courses
Deep learning:
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Theories of Deep Learning
[lectures],
Hatef Monajemi, et al., Stanford University
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ConvNet for visual recognition,
Fei-Fei Li, et al., Stanford University
-
Deep Learning,
Nando de Freitas, Oxford University
-
Deep Learning,
Amini et al., MIT
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Practical Deep Learning For Coders,
fast.ai
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Machine Learning Crash Course,
Google
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Intro to neural nets,
Hugo Larochelle, Université de Sherbrooke
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Deep Unsupervised Learning, Pieter Abbeel, UC berkeley, Spring 2019
Deep reinforcement learning:
Fundations:
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Intro to Machine Learning,
Tom Mitchell, CMU
- Convex Optimization
A
B
, Stephen P. Boyd, Stanford
-
Bayesian Statistics,
Nicholas Zabaras, University of Notre Dame
-
Statistical Learning Theory and Applications
[lectures],
Tomaso Poggio, et al., MIT
-
Statistical Machine Learning,
Ryan Tibshirani, Larry Wasserman, CMU
-
Machine Learning the Future,
Cornell Tech and Cornell
Books
Other resources
Frameworks
Other stuff