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Nice to meet you, I'm Anthony handwave

  • 💻 I'm currently learning Java, Ruby and Linux OS.
  • 📚 I studied Master of Data Science @ University of Sydney
  • 🙌 Currently SDE I @ AWS
  • 🎷 I listen to Cafe Jazz when I code
Be Humble, Stay Curious

2024 Goals

  • 💪 Get better at software designs
  • 🚀 Start contributing to Open Source
  • ⚡ Write cleaner code
  • 🚧 Personal Portfolio - Coming Soon!

Connect with me:

linkedin   twitter


Lanugage and Tools:

Web Development:

vsc   html5   css3   javscript   react   git   npm   jest   testing-library  

Machine Learning | Data Science:

jupyter   pycharm   python   numpy   scikitlearn   scipy   postgresql   tensorflow   pytorch  



Anurag's GitHub stats

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anthony's Projects

99bottles icon 99bottles

working on the js files based on the book 99 bottles of OOP

ai_sudoku_solver icon ai_sudoku_solver

Personal Project - creating a AI Sudoku Solver which involve end-to-end process from data collection all the way to deployment

android_data icon android_data

Some Android learning materials, hoping to help you learn Android development.

auction-eleven-bot icon auction-eleven-bot

A competition where you build bots to maximise score by recognising ally bots, outbid opponents while trying to identify their strategies

dad-joke icon dad-joke

basic practice on API usage - based on the API project from Colt Steele's Udemy course

docusaurus icon docusaurus

Easy to maintain open source documentation websites.

info-site icon info-site

a mini-project to learn about using node on server side javascript

is-it-a-cat icon is-it-a-cat

A personal goal to make a good image recognition model of cats! Also, as a practical exercise of using my preliminary knowledge in machine learning

kaggle-hungry-geese icon kaggle-hungry-geese

Kaggle Competition focusing on Reinforcement Learning. Kaggle has taken this classic in the video game industry and put a multi-player, simulation spin to the classic game Snake. The goal is to create an AI agent to play against others and survive the longest.

kaggle-tabular_playground_series_feb_2021 icon kaggle-tabular_playground_series_feb_2021

predicting a continuous target based on a number of feature columns given in the data. All of the feature columns, cat0 - cat9 are categorical, and the feature columns cont0 - cont13 are continuous.The dataset is used for this competition is synthetic, but based on a real dataset and generated using a CTGAN. The original dataset deals with predicting the amount of an insurance claim. Although the features are anonymized, they have properties relating to real-world features.

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