Type: User
Company: Sleep and Cognition Laboratory, National University of Singapore
Bio: Data Science enthusiast learning and applying data science & machine learning techniques to improve population health, sleep, and psychological well-being
Location: Singapore
teyang-lau's Projects
Attribute-based Encryption
Conducted customer sales segmentation and affinity analysis on chip sales to identify groups to target for advertisements and promotions.
Building a recommender system for coffee enthusiasts in Singapore, accompanied with a dashboard!
Exploration of Singapore mobility and search trends during COVID-19
Clustered >120k days of Fitbit data from 1.8k+ individuals to identify 4 subgroups of Singaporean working adults differentially susceptible to unhealthy behaviors during COVID-19
Classify real disaster tweets using different sequence models like LSTM, Bi-directional LSTM with attention, and transformers (BERT) with best accuracy of 84%
Classifying pictures into 120 dog breeds using Convolutional Neural Networks and transfer learning achieving 88% accuracy
Engineering MLOps
:zap: Dynamically generated stats for your github readmes
Building a recommendation system for Google Play games using content-based and collaborative filtering models
Predicted and identified the drivers of Singapore HDB resale prices (2015-2019) with 0.96 Rsquare & $20,000 MAE. Web app deployment using Streamlit for user price prediction.
Predicted heart disease using different machine learning models, with best model achieving 85% F1 score
Predicted melanoma in Kaggle competition by ensembling EfficientNets and meta-data, achieving AUROC of 92%
MLOps End-to-End Example using Amazon SageMaker Pipeline, AWS CodePipeline and AWS CDK
End-to-end MLOps Using MLflow for ML lifecycle, including data validation, processing, model training, evaluation, validation and deployment
Creating new artistic style pictures by blending own pictures with the style of other paintings using ConvNets
Detecting Pneumonia in chest X-Ray scans using Convolutional Neural Networks with a F1-score of 92%
A python module to support the use of the IBE, ABE, and PBE family of asymmetric encryption schemes.
This repo is for SMU Course CS611 on Machine Learning Engineering
Contains my Tableau Visualization Dashboard Projects