There are six snippets of code that made deep learning what it is today. Coding the History of Deep Learning on Floydhub' s blog 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