phelixh / ann-fundamentals

This is the repository for D-Lab’s Artificial Neural Network (ANN) Fundamentals in Python workshop. These materials were authored and contributed by [Qingkai Kong](http://seismo.berkeley.edu/qingkaikong/).

Artificial Neural Network (ANN) Fundamentals

This is the repository for D-Lab’s Artificial Neural Network (ANN) Fundamentals in Python workshop. These materials were authored and contributed by Qingkai Kong based on several of his excellent blog posts:

Machine learning 1 - What is machine learning and real world example
Machine learning 2 - Types of Machine Learning
Machine learning 3 - Artificial Neural Networks - part 1- Basics
Machine learning 4 - Artificial Neural Networks - part 2- Step by step implement Perceptron
Machine learning 5 - Artificial Neural Networks - part 3- Step by step implement Muti-Layer Perceptron
Machine learning 6 - Artificial Neural Networks - part 4- sklearn MLP classification example
Machine learning 9 - More on Artificial Neural Network

Content outline:

• Gentle introduction
  • What is machine learning?
  • History of artificial neural networks (ANN)
  • Overview of ANNs - how they work
• Step by step instructions for building ANN
  • Perceptron
  • Backpropagation
  • Bias
  • Activation function
  • Calculating error example
• Real world example
  • scikit learn