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ai-102-aiengineer

Lab files for AI-102 - AI Engineer

annotator-app

This flask app is a simple personal project (done by Andrew Tan[@a-tanman] and myself) that is meant to make it easier to label/annotate text data for creating datasets for supervised machine learning.

difference-of-gaussian-edge-texture-based-background-modeling-for-dynamic-traffic-conditions

Note: This is a very old Visual 2005 project which has not been tested to work with later versions of Visual Studio. Use at your own risk.

discriminative-robust-local-binary-and-ternary-patterns

Contains the codes for Discriminative and Robust Local Binary Pattern and Discriminative and Robust Local Ternary Pattern for object recognition developed by me during my PhD studies.

extended-histogram-of-gradients

Contains the codes for Extended Histogram of Gradients for object recognition developed by me during my PhD studies.

gds-webinar-scale-demo

Demo for GDS 2022 February Webinar

gpt-2

Code for the paper "Language Models are Unsupervised Multitask Learners"

gpt-3

GPT-3: Language Models are Few-Shot Learners

graph-book

The Code Examples and Notebooks for The Practitioners Guide to Graph Data

hdb-resale-geekout

identifying-commuter-travel-patterns-in-bus-services

A project I did with Land Transport Authority, a statutory board, whose main role is to manage the transportation infra of Singapore which includes public transport like bus and trains. The agency was interested to understand how the bus services were being utilized by commuters during peak hours and if interventions could be introduced to further enhance commuter experience on bus services e.g. shorter waiting time, faster trips with skipping of bus stops etc. This required understanding archetypes of travel patterns by commuters in bus services. This project is an extension of what was previously done here: https://blog.data.gov.sg/fingerprint-of-a-bus-route-73e5be53dcf0

interpret

Fit interpretable models. Explain blackbox machine learning.

knapsack-solution-for-resource-allocation

A solution for resource allocation based on limited constraints

lstm-sentiment-analysis

Sentiment Analysis with LSTMs in Tensorflow

machine-learning-with-python

Python codes for common Machine Learning Algorithms

ml-pipeline-generator-python

ML Pipeline Generator is a tool for generating end-to-end pipelines composed of GCP components so that any customer can easily migrate their local ML models onto GCP and start realizing the benefits of the cloud quickly.

mlflow-example

An example MLflow project

mlopsworld2020-kubeflow

workshop materials for the mlopsworld 2020

mlopsworld2020-mlflow

mlflow workshop material for mlopsworld 2020

mslearn-ai900

Lab files for AI-900: Azure AI Fundamentals

mslearn-dp100

Lab files for Azure Machine Learning exercises

notebooks-contrib

RAPIDS Community Notebooks

optical-flow-histogram-features-for-anomaly-movements-in-video

This repository contains codes for a project I did where we detect hypermotor seizures in an unsupervised environment.

recommenders

Best Practices on Recommendation Systems

reinforcement-learning-an-introduction

Python Implementation of Reinforcement Learning: An Introduction

spark-rapids

Spark RAPIDS plugin - accelerate Apache Spark with GPUs

supervised-classification-of-text-categories

This repo describes a supervised approach to text classification using different features and classifiers. This, obviously, is good to use if there is labelled data available.

topic-modeling-with-automated-determination-of-the-number-of-topics

My version of topic modelling using Latent Dirichlet Allocation (LDA) which finds the best number of topics for a set of documents using ldatuning package which comes with different metrics