Neural Networks

A brief introduction to Machine Learning focusing on Neural Computation

Syllabus

  1. Introduction to Machine Learning
  2. Logistic and Linear Regression
  3. Perceptron
  4. Multi-Layer Perceptron
  5. Recursive Neural Networks
  6. Clustering
  7. Radial Basis Function Networks
  8. Self Organizing Maps

Reference

  1. Neural Networks and Learning Machines, Simon Haykin, 2009
  2. Pattern Recognition and Machine Learning, Bishop, Springer, 2006

Python Notebooks

  1. Linear Regression - Toy Example
  2. Linear Regression - Housing Problem
  3. Logistic Regression - 0/1 MNIST

Material

  1. Python Online Material
  2. Docker Installation Manual - Windows
  3. Docker Installation Manual - Linux
  4. Docker Installation Manual - MAC
  5. Tensorflow Documentation