How to Train a Neural Net
Path step 2: Analyzes stochastic gradient descent, loss landscapes, and adaptive preconditioning in deep networks.
This session explains neural network training via stochastic gradient descent (SGD), backpropagation, and automatic differentiation. It highlights their role in differentiable programming.
AI & MLMathematicsDeep LearningProbability & Information TheoryConvex OptimizationNeural Network Training
MIT 6.7960 Deep Learning, Fall 2024
Instructor: Sara Beery
View the complete course: https://ocw.mit.edu/courses/6-7960-deep-learning-fall-2024/
YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63URZnh5iqBzDTDYPUTQT-8
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