semutter's repositories
Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising
Awesome Deep Learning papers for industrial Search, Recommendation and Advertising. They focus on Embedding, Matching, Ranking (CTR and CVR prediction), Post Ranking, Multi-task Learning, Graph Neural Networks, Transfer Learning, Reinforcement Learning, Self-supervised Learning and so on.
bandit_algo_evaluation
Offline evaluation of multi-armed bandit algorithms
bandits
Multi-Armed Bandit algorithms applied to the MovieLens 20M dataset
connected-component
Map Reduce Implementation of Connected Component on Apache Spark
courses
fast.ai Courses
dlrm
An implementation of a deep learning recommendation model (DLRM)
glog
C++ implementation of the Google logging module
Grokking-the-System-Design
Grokking the system design interview course materials
guava
Google core libraries for Java
gym
A toolkit for developing and comparing reinforcement learning algorithms.
iBook
收藏一些电子书
Personalized-News-Recommendation
Multi Armed Bandits implementation using the Yahoo! Front Page Today Module User Click Log Dataset
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 ;)
python-patterns
A collection of design patterns/idioms in Python
pytorch-best-practice
A Guidance on PyTorch Coding Style Based on Kaggle Dogs vs. Cats
RecBole
A unified, comprehensive and efficient recommendation library
reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
semutter.github.io
github page
spacemacs
A community-driven Emacs distribution - The best editor is neither Emacs nor Vim, it's Emacs *and* Vim!
spring-framework
Spring Framework
SpringAll
循序渐进，学习Spring Boot、Spring Boot & Shiro、Spring Cloud和Spring Security，博客Spring系列源码