Currently I am leading artificial intelligence with my colleagues in ensemblecap.ai, an AI hedge fund based in Singapore. I am also an NVIDIA Deep Learning Institute instructor enabling developers, data scientists, and researchers leverage on deep learning to solve the most challenging problems. In my leisure time, I dive into computer vision research, in particular Visual Question Answering (VQA) with researchers in NUS and MILA.

My passion for enabling anyone to leverage on deep learning has led to the creation of Deep Learning Wizard where I have taught and still continue to teach thousands of students in more than 60 countries around the world.

I was previously conducting research in deep learning, computer vision and natural language processing in NExT Search Centre led by Professor Tat-Seng Chua that is jointly setup between National University of Singapore (NUS) and Tsinghua University and is part of NUS Smart Systems Institute. During my time there, I managed to publish in top-tier conferences and workshops like ICML.

Oh yes! You can check out some of my cool stickman comics on Machine Learning if you are looking to chill with my stickman.

The Purpose of Artificial Intelligence

John Keynes predicted we would only work 15 hours a week. Yup, you heard it! I believe we can do that with even fewer stupendously productive hours. We can then spend the rest of our time doing other awesome things like Black Water Rafting. I bet you have never heard of that.

We can and will reach there by improving machine intelligence that can directly and indirectly improve people’s lives.


Neural Optimizers with Hypergradients for Tuning Parameter-Wise Learning Rates, ICML 2017

Deep Learning Courses

These are some of the courses I created that will gradually build up your deep learning capabilities.
Main Course Website, Deep Learning Wizard
Practical Deep Learning with PyTorch, Deep Learning Wizard

Past Talks

Meta Learning, AutoML, ICML, Sydney, 2017
Deep Learning for Self-Driving Cars and Medical Diagnostics, NVIDIA, Singapore, 2017
Scalable Hyperparameter Optimization, REWORK Deep Learning Summit, Singapore, 2017

Active Projects

This is basically “the Google” for searching code for computer science papers on arXiv. It’s currently concentrated on deep learning and machine learning. I started this companion website to arXiv.org to encourage reproducible research. You can easily search for code that are implemented by the authors themselves or often by others.

The Incredible PyTorch
This is an awesome curated list of tutorials, papers, projects, communities and more relating to PyTorch.

A Deep Learning Amazon Web Service (AWS) AMI that is open, free and works. Run any deep learning framework in less than 5 minutes including TensorFlow, Keras, PyTorch, Theano, MXNet, CNTK, Torch, and Caffe.

Past Projects

Residual Networks with TensorFlow

Wide Residual Networks with TensorFlow

Large Scale Identification of Multiple Digits from Real-world Images with Convolutional Neural Networks (CNN)

Training a Smart Cab (Reinforcement Learning)

Identifying Customer Segments (Unsupervised Learning)

Building a Student Intervention System (Supervised Learning)

Predicting Boston House Prices

Past Articles

The Great Conundrum of Hyperparameter Optimization, REWORK, 2017


Global Merit Scholarship 2014-2018, NUS
NUS top scholarship with only 4 awarded in NUS across all faculties for the year of my admission.
Full scholarship amounting to more than $100,000 covering tuition, allowance, accommodation, overseas trips and meals.

Dean’s List 2015/2016, NUS
Top 5% of my cohort.

I&E Practicum Award 2017, NUS
$10,000 Award.

Philip Yeo Innovation Fellowship 2017, NUS
$20,000 Award with a 1 year mentorship by Philip Yeo, Chairman of Spring Singapore.

Online Profiles


Languages, Libraries and Frameworks

Machine Learning Web Development Others
Python JavaScript LaTeX
C/C++ MeteorJS Bash Scripting
TensorFlow NodeJS MongoDB
TensorLayer   SQL
Keras   EViews
Scikit-learn   Stata
OpenCV   Adobe Illustrator
PyTorch   Adobe Photoshop


This is me attempting to look dapper with my blazer, albeit I rarely wear suits.
Ritchie Ng


I would like to thank all my readers for their encouraging participation on this Github page. I would also like to thank Github Pages for serving this respository of notes for free.

I would like to give full credit to the respective authors for their free courses and materials online like Andrew Ng, Data School and Udemy where my notes are from them. These personal notes are meant for my personal review but I have open-sourced my repository of personal notes as a lot of people found it useful.

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