Pengcheng-Wang

Pengcheng-Wang's Stars

• datawhalechina/pumpkin-book

  《机器学习》（西瓜书）公式详解

  23.8k622764.7k

• microsoft/unilm

  Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

  Language:Python19.5k2991.4k2.5k

• UKPLab/sentence-transformers

  State-of-the-Art Text Embeddings

  Language:Python14.8k1402.1k2.4k

• google/sentencepiece

  Unsupervised text tokenizer for Neural Network-based text generation.

  Language:C++10.1k1257431.2k

• huggingface/tokenizers

  💥 Fast State-of-the-Art Tokenizers optimized for Research and Production

  Language:Rust8.9k119977765

• Vay-keen/Machine-learning-learning-notes

  周志华《机器学习》又称西瓜书是一本较为全面的书籍，书中详细介绍了机器学习领域不同类型的算法(例如：监督学习、无监督学习、半监督学习、强化学习、集成降维、特征选择等)，记录了本人在学习过程中的理解思路与扩展知识点，希望对新人阅读西瓜书有所帮助！

  7.2k21091.9k

• facebookresearch/pytext

  A natural language modeling framework based on PyTorch

  Language:Python6.3k168135799

• cvxpy/cvxpy

  A Python-embedded modeling language for convex optimization problems.

  Language:C++5.3k1231.5k1.1k

• erikbern/ann-benchmarks

  Benchmarks of approximate nearest neighbor libraries in Python

  Language:Python4.9k117207729

• nmslib/hnswlib

  Header-only C++/python library for fast approximate nearest neighbors

  Language:C++4.3k64367630

• wzhe06/Ad-papers

  Papers on Computational Advertising

  Language:Python4.2k34821.2k

• dedupeio/dedupe

  :id: A python library for accurate and scalable fuzzy matching, record deduplication and entity-resolution.

  Language:Python4.1k120810549

• nmslib/nmslib

  Non-Metric Space Library (NMSLIB): An efficient similarity search library and a toolkit for evaluation of k-NN methods for generic non-metric spaces.

  Language:C++3.4k93431448

• pytorch/botorch

  Bayesian optimization in PyTorch

  Language:Jupyter Notebook3.1k51515390

• facebookresearch/XLM

  PyTorch original implementation of Cross-lingual Language Model Pretraining.

  Language:Python2.9k56334495

• tensorflow/ranking

  Learning to Rank in TensorFlow

  Language:Python2.7k97319473

• facebook/Ax

  Adaptive Experimentation Platform

  Language:Python2.3k69733303

• curiousily/Getting-Things-Done-with-Pytorch

  Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BER

  Language:Jupyter Notebook2.3k5122625

• microsoft/DeBERTa

  The implementation of DeBERTa

  Language:Python2k42123222

• zhougr1993/DeepInterestNetwork

  Language:Python1.6k4090559

• kamalkraj/BERT-NER

  Pytorch-Named-Entity-Recognition-with-BERT

  Language:Python1.2k2398278

• harvardnlp/pytorch-struct

  Fast, general, and tested differentiable structured prediction in PyTorch

  Language:Jupyter Notebook1.1k335592

• dorianbrown/rank_bm25

  A Collection of BM25 Algorithms in Python

  Language:Python985103183

• cvxopt/cvxopt

  CVXOPT -- Python Software for Convex Optimization

  Language:C97839186209

• google-research/recsim

  A Configurable Recommender Systems Simulation Platform

  Language:Python7393730128

• msnews/MIND

  Microsoft News Dataset

  Language:Python10961229

• flaviovdf/fpmc

  Implementation of the Factorizing Personalized Markov Chains for Next-Basket Recommendation

  Language:Python673725

• cgartrel/nonsymmetric-DPP-learning

  PyTorch implementation of nonsymmetric determinantal point process (DPP) learning.

  Language:Python23425

• Stanford-ILIAD/DPP-Batch-Active-Learning

  Companion code to the preprint: E Bıyık, K Wang, N Anari, D Sadigh, "Batch Active Learning using Determinantal Point Processes". arXiv preprint arXiv:1906.07975, Dec. 2019.

  Language:Jupyter Notebook13702

• kzkadc/ranknet

  PyTorch and Chainer implementation of RankNet

  Language:Python10100