bzheng6's Stars
kilimchoi/engineering-blogs
A curated list of engineering blogs
py-why/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.
scikit-learn/scikit-learn
scikit-learn: machine learning in Python
jphall663/awesome-machine-learning-interpretability
A curated list of awesome responsible machine learning resources.
wangyongjie-ntu/Awesome-explainable-AI
A collection of research materials on explainable AI/ML
google/lightweight_mmm
LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.
donnemartin/system-design-primer
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
karanpratapsingh/system-design
Learn how to design systems at scale and prepare for system design interviews
konosp/propensity-score-matching
gustavobramao/robyn_api_meta_hackathon
Meta APAC Robyn Hackathon 2022
microsoft/SparseSC
Fit Sparse Synthetic Control Models in Python
adilkhash/Data-Engineering-HowTo
A list of useful resources to learn Data Engineering from scratch
cjhutto/vaderSentiment
VADER Sentiment Analysis. VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media, and works well on texts from other domains.
SooyeonWon/customer_analytics_fmcg
Customer & Purchase Analytics using Segmentation, Targeting, Positioning, Marketing Mix, Price Elasticity
drivendataorg/cookiecutter-data-science
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
google/CausalImpact
An R package for causal inference in time series
inovex/justcause
💊 Comparing causality methods in a fair and just way.
rguo12/awesome-causality-algorithms
An index of algorithms for learning causality with data
COPT-Public/COPT.jl
Julia interface for COPT (Cardinal Optimizer)
uber/orbit
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
lehaifeng/T-GCN
Temporal Graph Convolutional Network for Urban Traffic Flow Prediction Method
didi/ChineseNLP
Datasets, SOTA results of every fields of Chinese NLP
didi/ALITA
ALITA is a layer-based data analysis tool. The front-end see
shenweichen/AlgoNotes
【浅梦学习笔记】文章汇总:包含 排序&CXR预估，召回匹配，用户画像&特征工程，推荐搜索综合 计算广告，大数据，图算法，NLP&CV，求职面试 等内容
BIMK/PlatEMO
Evolutionary multi-objective optimization platform
qcappart/hybrid-cp-rl-solver
Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization
zhougr1993/DeepInterestNetwork
uber/causalml
Uplift modeling and causal inference with machine learning algorithms
google-research/tensorflow_constrained_optimization
datawhalechina/leedl-tutorial
《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases