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: I: Computational Graphs.


By | 2017-09-07T16:17:50+00:00 August 25th, 2017|Artificial Intelligence, Deep Learning, Machine Learning, Python, TensorFlow|4 Comments
  • Matt

    Thanks for the great article!

  • Great stuff , very useful. Im learning AI, more interested in reinforcement learning.

  • abhinash khare

    Really great article… keep it up, Maybe you want to divide it into series of lecture, a blog for each algorithm.

    • Daniel

      Thanks for the tip, that’s what I’ve done now 🙂