Applied Ml
eugeneyan
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
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33–48 / 127
Candidates in this shortlist, not the full registry. GitHub stars belong to repositories, not individual skills.
Results: 127
eugeneyan
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
donnemartin
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumP…
d2l-ai
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Camb…
ZuzooVn
A complete daily plan for studying to become a machine learning engineer.
mrdbourke
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
NLP-LOVE
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现,也是作为一个算法工程师必会的理论基础知识。
sktime
A unified framework for machine learning with time series
dotnet
ML.NET is an open source and cross-platform machine learning framework for .NET.
catboost
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python,…
doccano
Open source annotation tool for machine learning practitioners.
afshinea
VIP cheatsheets for Stanford's CS 229 Machine Learning
h2oai
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeli…
guess-js
🔮 Libraries & tools for enabling Machine Learning driven user-experiences on the web
vwxyzjn
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)