Course Title : Neural Networks with Tensorflow

Instructor : Sanasam Ranbir Singh
Teaching Assistant: Th. Jennil Singh

Week 2: Introduction to Neural Network

Reference Books:

  1. Neural Networks and Learning Machines by Simon Haykin ( click)

Lessons

  1. Lesson 1: Neural Network and Human Brain ( PPT)
  2. Lesson 2: Multilayer Perceptron ( PPT)
  3. Lesson 3: Parameters of Multi-layer perceptron ( PPT)
  4. Lesson 4: Understanding Backpropagation ( PPT)
  5. Lesson 5: Loss Functions and Their Gradient estimates
    1. Mean Square Loss function and its gradient( PPT)
    2. Cross entropy loss functions and its gradient( PPT)
  6. Lesson 6: Activation Functions and Theirs Gradient Estimates ( PPT)

Sample Codes

  1. Understanding Forward Pass in MLP( click)
  2. Understanding different Activation Functions( click)
  3. Understanding dirivatives of different Activation Functions( click)
  4. Understanding Backpropagation through program( click)