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hyperlearn
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.sciblox
sciblox - Easier Data Science and Machine LearningAI_Lectures_2017
Data Science Society of UNSW Lecture SeriesGov_Hack_2017
We used NSW Air Quality data, health data, transport OPAL congestion data and also some novel disease spreading algorithms to try model and find correlations between Air Quality, Congestion and Influenza rates.Markovian_SIR_Deaths_Model
I noticed that traditional methods to predict a disease outbreak was by performing sentiment analysis on Twitter posts and Google Search terms. Unfortunately, these methods were inadequate, as Twitter and Google is not popular in all countries. So, I created a system to model and predict outbreaks without the need for social media. The system was able to update the probabilities of a virus from spreading from A to B in real time, and I plan to release it to the public next year. I also used Machine Learning and Deep Learning to predict larger long-term virus trends with Google Trends, and this acted as a validator for the MSIRD model.Reversing_Markov_Chains
Sometimes we want to โreverseโ a Markov Chain process. Taking the inverse of the transition matrix allows this to work, but the inverse result is not a transition matrix. If I wanted to model a population going to work, and then going back home, negative and greater than 1 probabilities in the inverse matrix will cause issues. I propose a method to compute the โinverseโ of a transition matrix, and the result is still a transition matrixHealth_Hack_2017
We developed a data mining solution to scrape data from multiple sources to get the latest and greatest information about health grants. AND - we designed a cool Jupyter Notebook Solution to visualise our 2nd challenge- to get data constantly from a source, and show it in PlotlyAI_Lab_2018
danielhanchen.github.io
A collection of machine learning notesMBS_Datathon_2017
We created a new Health Rating system that aggregated data from QANTAS, ABS, Victoria Health and supermarket data to reveal correlations between them. We got Special Commendations for our great work!UNSW_2025_Degree_Recommendation
aeros
Project Aeros aims to optimise data science processes in Python, and provides the user with easy to use functions and APIsUNSW_MARK_AI
danielhanchen
game2019
cria
Finetuning LLaMA with cleaned datasetsLove Open Source and this site? Check out how you can help us