Pinned Repositories
approximateinference
NIPS workshop on Advances in Approximate Bayesian Inference
ballr
Interactive NBA Shot Charts with R and Shiny
basketball
BasketballData
benchm-ml
A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).
Big-Data-Bowl
Homepage for the National Football League's Big Data Bowl
cracking-the-data-science-interview
Resources for Oreilly's "Cracking the Data Science Interview" video series.
lucaswu17.github.io
https://lucaswu17.github.io/
My-Project
Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
lucaswu17's Repositories
lucaswu17/lucaswu17.github.io
https://lucaswu17.github.io/
lucaswu17/My-Project
lucaswu17/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
lucaswu17/approximateinference
NIPS workshop on Advances in Approximate Bayesian Inference
lucaswu17/ballr
Interactive NBA Shot Charts with R and Shiny
lucaswu17/basketball
lucaswu17/BasketballData
lucaswu17/benchm-ml
A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).
lucaswu17/Big-Data-Bowl
Homepage for the National Football League's Big Data Bowl
lucaswu17/cracking-the-data-science-interview
Resources for Oreilly's "Cracking the Data Science Interview" video series.
lucaswu17/EPVDemo
Demo of NBA Expected Possession Value model
lucaswu17/FHH
lucaswu17/funFEM
:exclamation: This is a read-only mirror of the CRAN R package repository. funFEM — Clustering in the Discriminative Functional Subspace
lucaswu17/gganimate
Create easy animations with ggplot2
lucaswu17/hitchhikers-guide
The Hitchhiker's Guide to Data Science for Social Good
lucaswu17/machine-learning
:earth_americas: machine learning algorithms tutorials (mainly in Python3)
lucaswu17/NBA-Player-Movements
🏀 Visualization of NBA games from raw SportVU data logs
lucaswu17/nba_scorekeeper_bias
Code for the article "Adjusting for Scorekeeper Bias in NBA Box Scores" published in DMKD and presented at Sloan.
lucaswu17/open-data
Free football data from StatsBomb
lucaswu17/spark-nba-analytics
Analyzing NBA data using Spark 2.1
lucaswu17/SpatioTemporal
:exclamation: This is a read-only mirror of the CRAN R package repository. SpatioTemporal — Spatio-Temporal Model Estimation
lucaswu17/stat212b
Topics Course on Deep Learning UC Berkeley