jeongyoonlee Goto Github PK
Name: Jeong-Yoon Lee
Type: User
Company: Uber
Bio: Kaggler. CausalML. Father of Five.
Twitter: jeongyoonlee
Location: Los Angeles, CA
Blog: https://kaggler.com
Name: Jeong-Yoon Lee
Type: User
Company: Uber
Bio: Kaggler. CausalML. Father of Five.
Twitter: jeongyoonlee
Location: Los Angeles, CA
Blog: https://kaggler.com
Notes for adversarial learning
Amazon Employee Access Challenge
A Python library for audio data augmentation. Inspired by albumentations. Useful for machine learning.
Starting kit for AutoCV/AutoDL challenge
AutoGBT is used for AutoML in a lifelong machine learning setting to classify large volume high cardinality data streams under concept-drift. AutoGBT was developed by a joint team ('autodidact.ai') from Flytxt, Indian Institute of Technology Delhi and CSIR-CEERI as a part of NIPS 2018 AutoML for Lifelong Machine Learning Challenge.
Code for Adversarial Validation Approach to Concept Drift Problem in Automated Machine Learning Systems
A curated list of awesome adversarial machine learning resources
Playing with various deep learning tools and network architectures
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.).
Code for the Cornell Birdcall Identification competition
This is a barebones Node.js app using the Express framework.
Caffe: a Fast framework for neural networks. For the most recent version, check out branch dev. For a more stable version, check out branch master.
캐글 컴피티션 코드 정리 팁
Uplift modeling and causal inference with machine learning algorithms
resources for career development in data science
Resources for Data Science Process management
A collection of command-line tools that facilitate the obtaining, scrubbing, and exploring of data.
Decaf is DEPRECATED! Please visit http://caffe.berkeleyvision.org/ for Caffe, the new framework that has all the good things: GPU computation, full train/test scripts, native C++, and an active community!
The SDK for Jetpac's iOS Deep Belief image recognition framework
Code for Kaggle's Default Loan Prediction - Imperial College London challenge.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.