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algorithm-stone

ACM/LeetCode算法竞赛路线图，最全的算法学习地图！

angel

A Flexible and Powerful Parameter Server for large-scale machine learning

annoy

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

auto-gpt

An experimental open-source attempt to make GPT-4 fully autonomous.

awesome-causality-algorithms

An index of algorithms for learning causality with data

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 prediction, CVR prediction), Post Ranking, Transfer, Reinforcement Learning, Self-supervised Learning and so on.

awesome-network-embedding

A curated list of network embedding techniques.

causalml

Uplift modeling and causal inference with machine learning algorithms

computervision-recipes

Best Practices, code samples, and documentation for Computer Vision.

dataaug4nlp

Collection of papers and resources for data augmentation for NLP.

deepctr

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

deeptables

DeepTables: Deep-learning Toolkit for Tabular data

dlrm

An implementation of a deep learning recommendation model (DLRM)

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.

dplayer

:lollipop: Wow, such a lovely HTML5 danmaku video player

easyrec

A framework for large scale recommendation algorithms.

econml

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

ecosystem

Integration of TensorFlow with other open-source frameworks

euler

A distributed graph deep learning framework.

gnnpapers

Must-read papers on graph neural networks (GNN)

graphembedding

Implementation and experiments of graph embedding algorithms.deep walk,LINE(Large-scale Information Network Embedding),node2vec,SDNE(Structural Deep Network Embedding),struc2vec

graphormer

This is the official implementation for "Do Transformers Really Perform Bad for Graph Representation?".

lifetime_value

machinelearning

Basic Machine Learning and Deep Learning

mediapipe

Cross-platform, customizable ML solutions for live and streaming media.

mockingbird

🚀AI拟声: 5秒内克隆您的声音并生成任意语音内容 Clone a voice in 5 seconds to generate arbitrary speech in real-time

node2vec

paper_causalinference_abtest

因果推理&AB实验相关论文小书库

pikachu2

微信大数据2021 1st，qq浏览器2021 3rd，mind新闻推荐2020 1st，NAIC2020 AI+遥感影像 2nd

pylift

Uplift modeling package.