Hello!

I am Ritchie Ng, a machine learning engineer from the National University of Singapore (NUS) specializing in deep learning and computer vision.

Currently, I am conducting research in the areas of deep learning and hyperparameter optimization in NUS. And I live in University Town, NUS, as a Global Merit Scholar. Feel free to drop me a message if you are ever around NUS, I’ve a lot of free meal credits to spare!

I started this website to document my personal guides on machine learning. This website allows anyone to easily search for a guide I wrote. You can use the Google Search function to easily search for guides too.

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

Ongoing Projects

Gloqo
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.

TensorFlow AWS AMI, TFAMI
This is an open-source and actively-maintained Amazon Web Service AMI that allows anyone to work with Python, TensorFlow, Keras, TensorLayer, CUDA, cuDNN, and OpenAI Gym within 5 minutes.

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)
This project uses Python, TensorFlow, TensorBoard and OpenCV to recognize house numbers from Google’s Street View images.

Training a Smart Cab (Reinforcement Learning)
This project uses Python and PyGame to train a smart cab with reinforcement learning.

Identifying Customer Segments (Unsupervised Learning)
This project uses Python and Scikit-learn to implement PCA and clustering.

Building a Student Intervention System (Supervised Learning)
This project uses Python and Scikit-learn with an emphasis on Naive Bayes, Logistic Regression and Support Vector Machines.

Predicting Boston House Prices
This project uses Python and Scikit-learn with an emphasis on learning curves, complexity curves, GridSearchCV and RandomizedSearchCV.

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
    Adobe Photoshop

Headshot

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

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