zeetazhu

zeetazhu's Stars

• xifangczy/cat-catch

  猫抓 浏览器资源嗅探扩展 / cat-catch Browser Resource Sniffing Extension

  Language:JavaScript10.6k953

• simoninithomas/Deep_reinforcement_learning_Course

  Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch

  Language:Jupyter Notebook3.8k1.2k

• yuuwill/1024app-ios

  草榴官方客户端，小草客户端，iOS

  2.2k370

• wnzhang/rtb-papers

  A collection of research and survey papers of real-time bidding (RTB) based display advertising techniques.

  3.6k931

• checkcheckzz/system-design-interview

  System design interview for IT companies

  21.9k5.1k

• matplotlib/cheatsheets

  Official Matplotlib cheat sheets

  Language:Python7.4k898

• labuladong/fucking-algorithm

  刷算法全靠套路，认准 labuladong 就够了！English version supported! Crack LeetCode, not only how, but also why.

  Language:Markdown126k23.3k

• spotify/annoy

  Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk

  Language:C++13.4k1.2k

• lyhue1991/eat_tensorflow2_in_30_days

  Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋

  Language:Python10k2.5k

• HelloGitHub-Team/HelloDjango-blog-tutorial

  免费带你学 django 全栈！基于 django 2.2 的个人博客，初学者绝对不能错过的 django 教程！｡◕ᴗ◕｡

  Language:Python1.4k316

• greyli/helloflask

  Hello, Flask!

  1.9k2.5k

• princewen/tensorflow_practice

  tensorflow实战练习，包括强化学习、推荐系统、nlp等

  Language:Python6.8k3.3k

• thunlp/NRLPapers

  Must-read papers on network representation learning (NRL) / network embedding (NE)

  Language:TeX2.5k644

• ashishpatel26/Amazing-Feature-Engineering

  Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

  Language:Jupyter Notebook678257

• imsheridan/DeepRec

  推荐、广告工业界经典以及最前沿的论文、资料集合/ Must-read Papers on Recommendation System and CTR Prediction

  1k219

• jtoy/awesome-tensorflow

  TensorFlow - A curated list of dedicated resources http://tensorflow.org

  17.2k3k

• brendandburns/designing-distributed-systems-labs

  Labs for the Designing Distributed Systems book.

  Language:JavaScript1.3k335

• puncsky/system-design-and-architecture

  Learn how to design large-scale systems. Prep for the system design interview.

  Language:Makefile2.6k592

• xlvector/sw2v

  sparse word2vec

  Language:C++10834

• chaozh/MIT-6.824

  Basic Sources for MIT 6.824 Distributed Systems Class

  Language:Go3.2k623

• azl397985856/leetcode

  LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解，记录自己的leetcode解题之路。)

  Language:JavaScript54.9k9.5k

• wepe/efficient-decision-tree-notes

  高效决策树算法系列笔记

  Language:Python23047

• shenweichen/DeepCTR

  Easy-to-use,Modular and Extendible package of deep-learning based CTR models .

  Language:Python7.6k2.2k

• datawhalechina/pumpkin-book

  《机器学习》（西瓜书）公式详解

  24.3k4.8k

• yarny/gbdt

  Gradient boosting decision trees.

  Language:C++35860

• brightmart/bert_language_understanding

  Pre-training of Deep Bidirectional Transformers for Language Understanding: pre-train TextCNN

  Language:Python963211

• chrisjmccormick/word2vec_commented

  Commented (but unaltered) version of original word2vec C implementation.

  Language:C799228

• hongleizhang/RSPapers

  RSTutorials: A Curated List of Must-read Papers on Recommender System.

  6.3k1.4k

• wzhe06/Reco-papers

  Classic papers and resources on recommendation

  Language:Python3.3k806

• stanzhai/be-a-professional-programmer

  成为专业程序员路上用到的各种优秀资料、神器及框架

  9.7k2.1k