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Play bank data scientist and use regression discontinuity to see which debts are worth collecting.
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Python implementation of "Clustering Market Regimes Using the Wasserstein Distance" (Horvath et al., 2021). Detects bull/bear market regimes using optimal transport distance on return distributions. Includes WK-means algorithm, synthetic data generators, and validation metrics. Reproduces paper results on SPY data.
Introduction to Machine Learning Systems
Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.
A database of 450 Machine Learning (ML) system design case studies from 100+ companies.
Repositories
28My GitHub Profile
Python implementation of "Clustering Market Regimes Using the Wasserstein Distance" (Horvath et al., 2021). Detects bull/bear market regimes using optimal transport distance on return distributions. Includes WK-means algorithm, synthetic data generators, and validation metrics. Reproduces paper results on SPY data.
Introduction to Machine Learning Systems
Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.
A database of 450 Machine Learning (ML) system design case studies from 100+ companies.
Play bank data scientist and use regression discontinuity to see which debts are worth collecting.
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
This is Andrew NG Coursera Handwritten Notes.
Coding Practice Challenges
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C++, MySQL
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Awesome machine learning for combinatorial optimization papers.
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Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.
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Use joining techniques to discover the oldest businesses in the world.
Explore a dataset from Kaggle containing a century's worth of Nobel Laureates. Who won? Who got snubbed?
Load, clean, and visualize scraped Google Play Store data to gain insights into the Android app market.
Find the true Scala experts by exploring its development history in Git and GitHub.
Automatically generate keywords for a search engine marketing campaign using Python.
In this project, I apply Python to solve a real-world data science problem by using everything from lists and loops to pandas and matplotlib, manipulating raw data and drawing conclusions from plots that I create to discover if Netflix’s movies are getting shorter over time and which guest stars appear in the most popular episode of "The Office".
Use data manipulation and visualization to explore one of two different television broadcast datasets: The Super Bowl and hit sitcom The Office!
Use R to make art and create imaginary flowers inspired by nature