Deep Networks

Content

• Basics

  • Perceptron

  • Stochastic gradient descent

  • Loss functions and objectives

• Deep Networks

  • Layers and Invariances

  • Advanced objectives

• State and Structure

  • Optimization

  • Autoregressive Models & Hidden State

  • Toolkits

Supplementary material

• Deep Networks slides in PDF