danielhanchen/cria

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Language
Python
License
Apache License 2.0
Updated over 1 year ago

danielhanchen/cria

danielhanchen

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Finetuning LLaMA with cleaned datasets

hyperlearn

2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

Jupyter Notebook

sciblox

sciblox - Easier Data Science and Machine Learning

Microsoft_Hack_2017

Created a Machine Learning system to predict if someone is going to suicide, and proposed some mechanisms to counter and help potential victims.

Jupyter Notebook

AI_Lectures_2017

Data Science Society of UNSW Lecture Series

Gov_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.

Jupyter Notebook

Reversing_Markov_Chains

Sometimes we want to ”reverse” 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 ”inverse” of a transition matrix, and the result is still a transition matrix

Health_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 Plotly

Jupyter Notebook

AI_Lab_2018

danielhanchen.github.io

A collection of machine learning notes

MBS_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

Jupyter Notebook

aeros

Project Aeros aims to optimise data science processes in Python, and provides the user with easy to use functions and APIs

UNSW_MARK_AI

Jupyter Notebook

danielhanchen

game2019