sandman13

sandman13's Stars

• scutan90/DeepLearning-500-questions

  深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06

  Language:JavaScript54.7k2.2k18915.9k

• zergtant/pytorch-handbook

  pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行

  Language:Jupyter Notebook20.3k531835.4k

• afatcoder/LeetcodeTop

  汇总各大互联网公司容易考察的高频leetcode题🔥

  18.7k292642.7k

• taizilongxu/interview_python

  关于Python的面试题

  Language:Shell16.6k853505.5k

• NLP-LOVE/ML-NLP

  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。

  Language:Jupyter Notebook16k385394.5k

• Dod-o/Statistical-Learning-Method_Code

  手写实现李航《统计学习方法》书中全部算法

  Language:Python11k310302.9k

• rushter/MLAlgorithms

  Minimal and clean examples of machine learning algorithms implementations

  Language:Python10.7k423281.8k

• google/sentencepiece

  Unsupervised text tokenizer for Neural Network-based text generation.

  Language:C++10.2k1277481.2k

• wangzhiwubigdata/God-Of-BigData

  专注大数据学习面试，大数据成神之路开启。Flink/Spark/Hadoop/Hbase/Hive...

  9.7k33203.1k

• shenweichen/DeepCTR

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

  Language:Python7.6k1783692.2k

• hongleizhang/RSPapers

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

  6.2k33441.3k

• shenweichen/GraphEmbedding

  Implementation and experiments of graph embedding algorithms.

  Language:Python3.7k6365994

• aditya-grover/node2vec

  Language:Scala2.6k63101913

• wangshusen/RecommenderSystem

  2.4k276358

• mJackie/RecSys

  计算广告/推荐系统/机器学习(Machine Learning)/点击率(CTR)/转化率(CVR)预估/点击率预估

  1.9k701437

• guyulongcs/Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising

  Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Ranking (CTR/CVR prediction), Post Ranking, Large Model (Generative Recommendation, LLM), Transfer learning, Reinforcement Learning and so on.

  Language:Python1.4k531225

• MaurizioFD/RecSys2019_DeepLearning_Evaluation

  This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

  Language:Python9823914248

• acbull/pyHGT

  Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on pytorch_geometric

  Language:Python7881453162

• RRdmlearning/Machine-Learning-From-Scratch

  常用机器学习的算法简洁实现

  Language:Python641185288

• Cantoria/dynamic-graph-papers

  Archive of Temporal Knowledge Reasoning in Social Network and Knowledge Graph

  42116264

• Hvass-Labs/TensorFlow-Tutorials-Chinese

  TensorFlow 中文教程 (Chinese Tutorials)

  Language:Jupyter Notebook395206143

• chuxuzhang/KDD2019_HetGNN

  code of HetGNN

  Language:Python389624102

• StatsDLMathsRecomSys/Inductive-representation-learning-on-temporal-graphs

  Language:Python29531662

• aravindsankar28/DySAT

  Representation learning on dynamic graphs using self-attention networks

  Language:Python27951544

• clhchtcjj/BiNE

  BiNE: Bipartite Network Embedding

  Language:Python22641580

• gregwchase/eyenet

  Identifying diabetic retinopathy using convolutional neural networks

  Language:Python195171576

• THUDM/MCNS

  Source code and dataset for KDD 2020 paper "Understanding Negative Sampling in Graph Representation Learning"

  Language:Python1116733

• sandman13/Personal_Recommendation_Action

  一些经典的个性化推荐算法的实现，从理论推导到实战

  Language:Python661025

• nebw/temporal_network_embeddings

  Learning of temporal network dynamics using recurrent neural networks

  Language:Python3200

• luhao2013/distributed_train

  分布式训练模型

  Language:Python1201