/iiccsss_intro2nnets

teaching material for my 2h graduate-level crash course on artificial neural networks

Primary LanguageJupyter Notebook

Introduction to Artificial Neural Networks and Gradient Descent

Teaching material for an advanced 2h course on neural networks I gave at the International Interdisciplinary Computational Cognitive Science Spring School in Freiburg, 2019 (http://iiccsss.org/)

Binder

Contents

The course introduces artificial neural networks as composition of linear and nonlinear functions and is divided into three sections:

  1. Maths Refresher
  2. Basics
    1. Linear Regression
    2. Logistic Regression
    3. (Stochastic) Gradient Descent
  3. Neural Networks
    1. Architecture
    2. Backpropagation Algorithm

I provide code examples in Python for the second and third section

Material

  • code
    contains code examples implemented as iPython notebooks

  • slides
    lecture slides

Contact

If you spot typos, have suggestions or would like to use the material, send me an email (firstname (dot) lastname (at) psy (dot) ox (dot) ac (dot) uk)