## Deep Learning From Scratch V: Multi-Layer Perceptrons

This is part 5 of a series of tutorials, in which we develop the mathematical and algorithmic underpinnings of deep neural networks from scratch and implement our own neural network library in Python, mimicing the TensorFlow API. Start with the first [...]

## Deep Learning From Scratch IV: Gradient Descent and Backpropagation

This is part 4 of a series of tutorials, in which we develop the mathematical and algorithmic underpinnings of deep neural networks from scratch and implement our own neural network library in Python, mimicing the TensorFlow API. Start with the first [...]

## Deep Learning From Scratch III: Training criterion

This is part 3 of a series of tutorials, in which we develop the mathematical and algorithmic underpinnings of deep neural networks from scratch and implement our own neural network library in Python, mimicing the TensorFlow API. Start with the [...]

## Deep Learning From Scratch II: Perceptrons

This is part 2 of a series of tutorials, in which we develop the mathematical and algorithmic underpinnings of deep neural networks from scratch and implement our own neural network library in Python, mimicing the TensorFlow API. Start with the first [...]

## Deep Learning From Scratch I: Computational Graphs

This is part 1 of a series of tutorials, in which we develop the mathematical and algorithmic underpinnings of deep neural networks from scratch and implement our own neural network library in Python, mimicing the TensorFlow API. Part I: Computational [...]

## Deep Learning From Scratch: Theory and Implementation

This is a multi-part series of tutorials, in which we develop the mathematical and algorithmic underpinnings of deep neural networks from scratch and implement our own neural network library in Python, mimicing the TensorFlow API. Start with the first part: [...]