Currently I am leading artificial intelligence with my colleagues in ensemblecap.ai, an AI hedge fund based in Singapore comprising quants and traders from JPMorgan. I have built the whole AI tech stack in a production environment with rigorous time-sensitive and fail-safe software testing powering multi-million dollar trades daily. Additionally, I co-run, as portfolio manager, our deep learning systematic portfolio, delivering positive annual returns since 2018.
I am also an NVIDIA Deep Learning Institute instructor leading all deep learning workshops in NUS, Singapore and conducting workshops across Southeast Asia.
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 more than 2000 students in over 60 countries around the world. The course is recognized by Soumith Chintala, Facebook AI Research, and Alfredo Canziani, Post-Doctoral Associate under Yann Lecun, as the first comprehensive PyTorch Video Tutorial.
I have taught Deep Learning Foundations with Alfredo Canziani at Rwanda, Africa for the African Masters in Machine Intelligence (AMMI) in 2018 supported by Google and Facebook.
In my free time, I’m into deep learning research on hyperspectral satellite imaging and financial time series with researchers in NUS, Montreal Institute for Learning Algorithms (MILA), New York University (NYU), African Institute for Mathematical Sciences (AIMS) and Hong Kong University of Science and Technology (HKUST). I am a research scholar in NExT (NUS).
I was previously conducting research in meta-learning for hyperparameter optimization for deep learning algorithms in NExT Search Centre that is jointly setup between National University of Singapore (NUS), Tsinghua University and University of Southampton led by co-directors Prof Tat-Seng Chua (KITHCT Chair Professor at the School of Computing), Prof Sun Maosong (Dean of Department of Computer Science and Technology, Tsinghua University), and Prof Dame Wendy Hall (Director of the Web Science Institute, University of Southampton).
I graduated from NUS where I was an NUS Global Merit Scholar, Chua Thian Poh Community Leadership Programme Fellow, Philip Yeo Innovation Fellow, and NUS Enterprise I&E Praticum Award recipient. I was awarded the IT Youth Leader of the Year Award in 2019.
Deep Learning Courses with Deep Learning Wizard
- These are some of the courses/tutorials I created that will gradually build up your deep learning capabilities. We are an NVIDIA Inception Partner based in Singapore.
- Deep Learning and Deep Reinforcement Learning Tutorials (Libraries: Pytho, PyTorch, Gym, NumPy and Matplotlib)
- Course Progression
- Linear Regression
- Logistic Regression
- Feedforward Neural Network
- Convolutional Neural Network (CNN)
- Recurrent Neural Network (RNN)
- Long Short-Term Memory (LSTM) network
- Derivative, Gradient and Jacobian
- Forwardpropagation, Backpropagation and Gradient Descent
- Learning Rate Scheduling
- Optimization Algorithms
- Weight Initialization and Activation Functions
- Supervised to Reinforcement Learning
- Markov Decision Processes and Bellman Equations
- Dynamic Programming
- Scalable Database Tutorials (Libraries: Apache Cassandra, Bash and Python)
- Natural Language Processing with Deep Learning, NVIDIA, Singapore, 2019
- Computer Vision with Deep Learning 2.0, NVIDIA, Singapore, 2019
- Deep Learning Fundamentals, Zenodo, 2018
- Neural Optimizers with Hypergradients for Tuning Parameter-Wise Learning Rates, AutoML, ICML, 2017
- Foundations of Deep Learning, African Masters of Machine Intelligence (AMMI), Google & Facebook, Kigali, Rwanda, November 2018
- AI and Unstructured Analytics in Fintech, Nanjing, China, November 2018 Post Link
- PyTorch Developer Conference, Facebook, San Francisco, USA, October 2018
- Hyperparameter Optimization with Neural Optimizers, Big Data & AI Leaders Summit, Singapore, September 2018
- Image Classification Workshop, NUS-NUH-MIT Datathon, NVIDIA, Singapore, July 2018
- Object Detection with DIGITS, NVIDIA, Singapore, June 2018
- 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
- 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
- The Incredible PyTorch, curated list of tutorials and projects in PyTorch
- DLAMI, deep learning Amazon Web Service (AWS) that’s free and open-source
IT Youth Leader of The Year 2019, Singapore Computer Society
Prestigious award for my industry, academic and charitable work in ensemblecap.ai, Deep Learning Wizard, NVIDIA and NUS
Chua Thian Poh Community Leadership Programme Fellow 2018, NUS
Established with generous gifts from Mr Chua Thian Poh, the Centre aims to nurture Singapore’s next generation of community leaders. These leaders will not only be intellectually engaged with social and community issues, but will also be passionate about addressing social and community challenges in Singapore.
Philip Yeo Innovation Fellowship 2017, NUS
Award with mentorship by Philip Yeo, Chairman of Spring Singapore.
I am fortunately also under the mentorship of Kiren Kumar (AMD, EDB) and Abel Ang (CEO, EDIS).
Valedictorian (Reserve) Class of 2018, NUS
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, and overseas trips.
I&E Practicum Award 2017, NUS
Dean’s List 2015/2016, NUS
Top 5% of my cohort.
Languages, Libraries and Frameworks
|Machine Learning||Database||General Programming|
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.
Take note that I’m currently concentrating entirely on building materials for Deep Learning with PyTorch from mastering deep learning, to deploying deep learning algorithms in production, and to to solve many problems through Deep Learning Wizard.