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2019-autumn-recruitment-experience

2019届秋招面经集合

algorithm-base

专门为刚开始刷题的同学准备的算法基地，没有最细只有更细，立志用动画将晦涩难懂的算法说的通俗易懂！

arxiv-sanity-preserver

Web interface for browsing, search and filtering recent arxiv submissions

autoint

Implementation of AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

awesome-multimodal-ml

Reading list for research topics in multimodal machine learning

awesome-neural-logic

Awesome Neural Logic and Causality: MLN, NLRL, NLM, etc. 因果推断，神经逻辑，强人工智能逻辑推理前沿领域。

causalml

Uplift modeling and causal inference with machine learning algorithms

cluster_for_weibo_data

针对微博的话题聚类实现

ctr_algorithm

一些经典的CTR算法的复现; LR, FM, FFM, AFM, DeepFM，xDeepFM, PNN, DCN, DCNv2, DIFM, AutoInt, FiBiNet,DIN, DIEN ... （pytorch, tf2.0）

daily-interview

Datawhale成员整理的面经，内容包括机器学习，CV，NLP，推荐，开发等，欢迎大家star

data-competition-topsolution

Data competition Top Solution 数据竞赛top解决方案开源整理

dcgan-tensorflow

A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"

deep-autoencoders-for-collaborative-filtering

Using Deep Autoencoders for predictions of movie ratings.

deep-ctr-prediction

CTR prediction models based on deep learning(基于深度学习的广告推荐CTR预估模型)

deep-learning-for-causal-inference

Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflow 2.

deepctr

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

deepfeatinterp

Deep Feature Interpolation (CVPR 2017)

deeplearningbook-chinese

Deep Learning Book Chinese Translation

deeprecommender

Deep learning for recommender systems

dien

dnn_ctr

The framework to deal with ctr problem。The project contains FNN,PNN,DEEPFM, NFM etc

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.

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.

fader_networks

faiss

A library for efficient similarity search and clustering of dense vectors.

fifa-worldcup-2018-prediction

Using Machine Learning to predict the winner of the 2018 FIFA World Cup.

game2vec

TensorFlow implementation of word2vec applied on https://www.kaggle.com/tamber/steam-video-games dataset, using both CBOW and Skip-gram.

gan-paper

We are trying to recurrent the paper Manipulating Images by Sliding Attributes

gbdt_lr

广告点击率(CTR)预测经典模型 GBDT + LR 理解与实践（附数据 + 代码）