Hello!
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. Also, I’m into natural language processing (NLP) research 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.
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
Upcoming Talks/Workshops
Object Detection with DIGITS, NVIDIA, Singapore, June 2018
Deep Learning Fundamentals Workshop 1, NVIDIA, Singapore, August 2018 (more details coming soon)
Deep Learning Fundamentals Workshop 2, NVIDIA, Singapore, September 2018 (more details coming soon)
Big Data & AI Leaders Summit, Singapore, September 2018
Key Papers
Neural Optimizers with Hypergradients for Tuning Parameter-Wise Learning Rates, ICML 2017
Past Talks/Workshops
Image Classification with DIGITS, NVIDIA, Singapore, May 2018
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
Past Projects
Residual Networks with TensorFlow
Wide Residual Networks with TensorFlow
Training a Smart Cab (Reinforcement Learning)
Identifying Customer Segments (Unsupervised Learning)
Building a Student Intervention System (Supervised Learning)
Predicting Boston House Prices
The Incredible PyTorch
This is an awesome curated list of tutorials, papers, projects, communities and more relating to PyTorch.
DLAMI
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 Articles
The Great Conundrum of Hyperparameter Optimization, REWORK, 2017
Awards
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 |
Headshot
This is me attempting to look dapper with my blazer, albeit I rarely wear suits.
Credits
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.