Deep Learning Overview

Posted on July 25, 2016


View my Deep Learning Overview : [Google Slides]
Deep Learning Research Projects: [Google Slides]

Beware, these things get out of date very quick. This presentation is from Oct 2016.

The outline of the talk:

  • Toy Neural Network
    • Loss Function
    • Stochastic Gradient Descent
    • Forward-pass (Neural Function Evaluation)
    • Backward-pass (Gradient of Neural function wrt to params)
  • Recent Progress
    • Convolutional Layer and its computations
    • Pooling Layer and its computations
    • Note on Non-linearity (ReLU, PReLU, Sigmoid, Tanh etc.)
    • Param initialization and recent progress
    • Note of Caffe and other alternatives
    • Commonly used Network Architectures
  • Recent Projects
    • My Work – MapNets
    • Deep Visualization
    • R-CNN
    • Generative Adversarial Networks
      • Bed Room image generation
      • Deep Art
      • Images which fool the imagenet models
    • Recurrent Nets
    • Reinforcement Learning
  • References
    • Deep Learning Book
    • Fei Fei Li’s CS251n @ Stanford
Posted in: Research Blog