Habits I Picked Up While Learning Machine Learning

June 26, 2019

This is a list of practices I adopted along the way that I think are worth sharing.


Transformer in Tensorflow - Attention Is All You Need

Feb 24, 2019

I coded this Transformer from scratch for learning. This is based on The Annotated Transformer by Harvard NLP, which uses PyTorch.

It is tested on a toy problem instead of NLP data to make things simpler.


Proximal Policy Optimization Algorithms - PPO in PyTorch

Feb 9, 2019

This is a re-implementation of my previous Tensorflow PPO code. I just coded it to try out PyTorch. This is also fully documented and should help someone trying to learn about PPO.


Lab: Organize Machine Learning Experiments

Dec 21, 2018

This library helps you organize machine learning experiments. It maintains TensorBoard summaries, checkpoints, produce pretty console outputs, and also adds a header with progress of experiments to python source files. It also has tools to plot custom charts based on TensorBoard summaries.


Deeq Q Learning in Tensorflow

June 16, 2018

I coded a DQN agent to play Atari. It is a stand alone implementation. I went through the Open AI DQN so it's very similar to it. I coded this also in a literate fashion similar to my previous PPO implementation.


Proximal Policy Optimization (PPO) in Tensorflow

June 3, 2018

I implemented a reinforcement learning agent using PPO to play Atari Breakout. It is a standalone implementation on TensorFlow.

I coded in a literate form with all the mathematical formula's etc, embedded in comments so that it can be used as a tutorial if any one wants to - and of course as a reference for my self.


Turn TensorFlow functions into mathematical notations and diagrams

March 24, 2018

I started working on a bunch of helper classes to use TensorFlow on Jupyter notebooks.

They provide nice diagrams and mathematical formulas as outputs based on the TensorFlow operations. It helps you understand the code better, and also acts as an inline help when coding.


Generative Adversarial Networks (Gaussian Distribution)

February 3, 2018

This is a very simple Generative Adversarial Network build with deeplearn.js on ObservableHQ.

I coded this as an experiment to try out ObservableHQ, because I've loved almost all the projects by its creators @jashkenas and @mbostock.


Vanilla LSTM with numpy

October 8, 2017

I implemented a Long short-term memory (LSTM) module on numpy from scratch. This is for learning purposes. The network is trained with stochastic gradient descent with a batch size of 1 using AdaGrad algorithm (with momentum).


Should we switch from CoffeeScript?

September 28, 2016

We are considering moving out codebase from CoffeeScript to TypeScript.