hetianbaicnn

hetianbaicnn's Stars

• youngyangyang04/leetcode-master

  《代码随想录》LeetCode 刷题攻略：200道经典题目刷题顺序，共60w字的详细图解，视频难点剖析，50余张思维导图，支持C++，Java，Python，Go，JavaScript等多语言版本，从此算法学习不再迷茫！🔥🔥 来看看，你会发现相见恨晚！🚀

  Language:Shell50.6k38023611.3k

• slundberg/shap

  A game theoretic approach to explain the output of any machine learning model.

  Language:Jupyter Notebook19.7k2532.3k3k

• microsoft/LightGBM

  A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

  Language:C++16.5k4333.4k3.8k

• tiangolo/typer

  Typer, build great CLIs. Easy to code. Based on Python type hints.

  Language:Python15.1k76324643

• marcotcr/lime

  Lime: Explaining the predictions of any machine learning classifier

  Language:JavaScript11.5k2636341.8k

• aws/amazon-sagemaker-examples

  Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

  Language:Jupyter Notebook10k2651.4k6.7k

• lyhue1991/eat_tensorflow2_in_30_days

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

  Language:Python9.9k269682.5k

• py-why/dowhy

  DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

  Language:Python7k137474922

• piglei/one-python-craftsman

  来自一位 Pythonista 的编程经验分享，内容涵盖编码技巧、最佳实践与思维模式等方面。

  6.8k19754963

• uber/causalml

  Uplift modeling and causal inference with machine learning algorithms

  Language:Python5k84393767

• lyst/lightfm

  A Python implementation of LightFM, a hybrid recommendation algorithm.

  Language:Python4.7k87503687

• andrewekhalel/MLQuestions

  Machine Learning and Computer Vision Engineer - Technical Interview Questions

  2.9k272488

• jayinai/data-science-question-answer

  A repo for data science related questions and answers

  Language:Jupyter Notebook2.4k881658

• tensorflow/recommenders

  TensorFlow Recommenders is a library for building recommender system models using TensorFlow.

  Language:Python1.8k49413273

• zhengjingwei/machine-learning-interview

  算法工程师-机器学习面试题总结

  1.3k121188

• nyu-dl/dl4marco-bert

  Language:Python475144888

• wetliu/energy_ood

  Language:Python39473564

• wangzhegeek/EGES

  Language:Python387933144

• hwwang55/MKR

  A tensorflow implementation of MKR (Multi-task Learning for Knowledge Graph Enhanced Recommendation)

  Language:Python3211010110

• AdeDZY/DeepCT

  DeepCT and HDCT uses BERT to generate novel, context-aware bag-of-words term weights for documents and queries.

  Language:Python31281946

• gaolinjie/awesome-recommender-systems

  A curated list of awesome resources about Recommender Systems.

  31121065

• HazyResearch/KGEmb

  Hyperbolic Knowledge Graph embeddings.

  Language:Python247211647

• snap-stanford/graphwave

  Language:Jupyter Notebook169541553

• sunzhuntu/Recurrent-Knowledge-Graph-Embedding

  This is for the knowledge graph embedding recommendation framework – RKGE

  Language:Python654821

• siyongxu/GNUD

  Source code for ACL 2020 paper “Graph Neural News Recommendation with Unsupervised Preference Disentanglement”

  Language:Python5911225

• ptannor/augboost

  AugBoost: Gradient Boosting Enhanced with Step-Wise Feature Augmentation (2019 IJCAI paper)

  Language:Python221012

• Med-ELOMARI/LightFM-Dataset-Helper

  python package to help preparing Dataframes (csv ... ) for LightFM module for easy Training

  Language:Python20334

• yongzx/SDEC-Keras

  Implementation of Semi-supervised Deep Embedded Clustering (SDEC) in Keras

  Language:Python17218

• AntonUBC/kaggle_flavours_of_physics

  Kaggle Competition: detect a rare decay phenomenon (τ → μμμ)

  Language:Python4205

• ptuls/movielens-diversity-metric

  Implementation of Spotify's Generalist-Specialist score on the MovieLens dataset.

  Language:Jupyter Notebook3201