There are six snippets of code that made deep learning what it is today. Coding the History of Deep Learning covers the inventors and the background to their breakthroughs. In this repo, you can find all the code samples from the story.

• The Method of Least Squares: The first cost function
• Gradient Descent: Finding the minimum of the cost function
• Linear Regression: Automatically decrease the cost function
• The Perceptron: Using a linear regression type equations to mimic a neuron
• Artificial Neural Networks: Leveraging backpropagation to solve non-linear problems
• Deep Neural Networks: Neural networks with more than one hidden layer