Reading 09: Multilayer Perceptrons, Gradient Descent, and Backpropagation

Readings

Videos

Notebooks

Readings

• • FCA - Sections 8.1.1 and 8.2
• • PML - Section 13.3
• • ISLP - Section 10.7
• • D2L - Section 5.3
• • UML - Section 20.6

Videos

• • Panopto
• • Harvard CS50 (16:00 - 39:00)
• • Stanford CS221 - SGD
• • Stanford CS221 - Backprop
• • MIT 6.034
• • SGD (StatQuest)
• • Chain Rule (StatQuest)
• • Backprop (StatQuest)
• • Building Micograd (Karpathy)
• Gradient descent, how neural networks learn | Deep Learning Chapter 2
• Backpropagation, intuitively | Deep Learning Chapter 3
• • Backpropagation calculus | Deep Learning Chapter 4

Notebooks

• • Numpy Backprop
• • Pytorch Computation Graphs (rasbt)

Blogposts

• • Backprop (Olah)
• • Backprop (Karpathy)