Machine learning tutorials

Tutorial: Neural ordinary differential equations

4th March 2021



Describing complex phenomena directly is difficult to do. In those situations, an alternative, implicit definition can often help us model the phenomenon and perform simulations of it.

Ordinary Differential Equations (ODEs) do this by describing how a system changes, that is, they present equations that capture the "dynamics" of the system.

In this tutorial, we will begin to explore what learning these dynamics through neural network training allows us to do. Examples include making density estimation through normalizing flows continuous and allowing time-series models to take in data sampled at irregular intervals.

Hand Gesture Recognition: Tutorial Project 1

18th February 2021


The majority of deaf-and-mute people use sign language produced by body actions such as hand gestures, body motion, eyes and facial expressions to communicate amongst each other and with non-impaired people in their daily life. However, it has become a barrier for mute and deaf communities which intend to integrate into society. To bridge the communication gap, a hand gesture recognition system for Sign Language Recognition (SLR) is required.

This project aims to design a real-time vision-based hand gesture recognition system with machine learning techniques, which potentially makes deaf-and-mute people life easier. In practice, signs are always continuously spelt words mixing both dynamic and static gestures, so the wanted recognition system should be able to recognize both dynamic and static gestures in ASL with promising accuracy.

Tutorial 4: Applications of Deep Learning

Hosted by Danny Kim

December 17th 2020

Learn more about the basics of using perceptrons, Digit Recogniser by TensorFlow/Keras and Pytorch on a practical level.

Tutorial notebook releases on

December 3rd, 2020.


Tutorial 3: Introduction to Deep Neural Networks

Hosted by Danny Kim

December 3rd 2020

Find out what perceptrons are, and how they can be implemented programmatically.


Get exposed to Tensorflow and Keras, one of the most widely used Deep Learning Frameworks.

Tutorial notebook releases on

November 19th, 2020.


Tutorial 2: Machine Learning Algorithms and Practices

Hosted by Danny Kim

November 19th 2020

Using scikit-learn, we'll cover some classical machine learning algorithms - from regression to support vector machines (SVM) and decision trees.

Tutorial notebook releases on

November 5th, 2020.


Tutorial 1: Numerical Computation and Visualisation for ML

Hosted by Danny Kim

November 5th 2020

Learn how to use Numpy for maths, Pandas for dataframes and Matplotlib for data visualisation.


Experience exploratory data analysis (EDA) as a preparatory step before diving into actual machine learning.

Tutorial notebook NOW AVAILABLE HERE




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