Name: Aaron Liftig
Type: User
Bio: Full Stack Developer -- Python, Javascript, C#. I'm interested in machine learning and data science. Feel free to reach out if you'd like to collaborate.
Location: Melbourne, Australia
Blog: https://www.linkedin.com/in/aaronliftig/
Aaron Liftig's Projects
An original build-a-chord guitar web app based on a 2018 Google Sheet diagram that I created. It is aimed at beginners as an alternative way to approach learning complex guitar chords.
Implementation of ADALINE algorithm
An original card game that combines the nostalgia of the game War with the strategy of Blackjack. Will use a reinforcement learning AI built in Pytorch.
In SQL Server, this query generates a table with consecutive dates and their corresponding business day from the start of each month
An individually derived expression that computes a strict upper bound of chess positions, and a generalization of part of that expression which finds the total number of piece combinations for an arbitrary number of piece types and counts.
A prototype of a probabilistic research model for a math professor. It is meant to simulate a white blood cell chasing a bacteria.
C# version of the PyDealer playing card library
Scripts to scrape AFL data from afltables.com and footywire.com. Data includes game, player bio, and player game data, including all of the historical data for players who were active from 2012 onward.
A more practical version of the MiniMax algorithm, prioritizing traps and challenging continuations over the objectively best line. Will be deployed natively into a chess engine.
Freelance projects, primarily Excel macros
Python code that displays the concept from Stand-up Maths and 3Blue1Brown's video.
Predictive models for AFL Tipping, Fantasy and Supercoach.
A predictive model for Horse Racing.
A simple package containing classes/methods for constructing decks of playing cards (standard 'French deck'). Could be used for a CLI game, or even a graphical game as well.
Python interpretation of Pokemon battles with extra features to make it more like the show. Includes scraped Pokemon Pokedex, stat, and move datasets.
A queuing simulator that uses the AsyncIO library
Ring appraisal machine learning model and Flask app
Code used on peak and pinnacle set research
An original algorithm for the Euclidean version of the Traveling Salesman Problem (ETSP), utilizing the midpoint of the convex hull edges.