MiniFlow is a library implemented as my own version of TensorFlow during studying Lesson 7 of Self Driving Car Nanodegree on Udacity.

TensorFlow is one of the most popular open source neural network libraries, built by the team at Google Brain over just the last few years.

Following the steps taught in the lesson, we can demystify two concepts at the heart of neural networks - backpropagation and differentiable graphs.

Backpropagation is the process by which neural networks update the weights of the network over time.

Differentiable graphs are graphs where the nodes are differentiable functions. They are also useful as visual aids for understanding and calculating complicated derivatives. This is the fundamental abstraction of TensorFlow - it's a framework for creating differentiable graphs.

With graphs and backpropagation, you will be able to create your own nodes and properly compute the derivatives. Even more importantly, you will be able to think and reason in terms of these graphs.

MiniFlow is a free software and may be redistributed under the terms specified in the LICENSE file.