YuyangZhangFTD's Stars
zergtant/pytorch-handbook
pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行
datasciencescoop/Data-Science--Cheat-Sheet
Cheat Sheets
pytorch/tutorials
PyTorch tutorials.
shenweichen/DeepCTR
Easy-to-use,Modular and Extendible package of deep-learning based CTR models .
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.
Kaggle/kaggle-api
Official Kaggle API
uber/causalml
Uplift modeling and causal inference with machine learning algorithms
hibayesian/awesome-automl-papers
A curated list of automated machine learning papers, articles, tutorials, slides and projects
facebookresearch/nevergrad
A Python toolbox for performing gradient-free optimization
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.
pytorch/botorch
Bayesian optimization in PyTorch
shenweichen/DeepCTR-Torch
【PyTorch】Easy-to-use,Modular and Extendible package of deep-learning based CTR models.
rguo12/awesome-causality-algorithms
An index of algorithms for learning causality with data
tensorflow/ecosystem
Integration of TensorFlow with other open-source frameworks
rixwew/pytorch-fm
Factorization Machine models in PyTorch
grf-labs/grf
Generalized Random Forests
qiaoguan/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)
wzhe06/SparkCTR
CTR prediction model based on spark(LR, GBDT, DNN)
rguo12/awesome-causality-data
A data index for learning causality.
logangraham/arXausality
A every-so-often-updated collection of every causality + machine learning paper submitted to arXiv in the recent past.
Minyus/causallift
CausalLift: Python package for causality-based Uplift Modeling in real-world business
scikit-garden/scikit-garden
A garden for scikit-learn compatible trees
napsternxg/awesome-causality
Resources related to causality
DataSystemsGroupUT/AutoML_Survey
GBDT-PL/GBDT-PL
Gradient Boosting With Piece-Wise Linear Trees
rsyi/pylift
Uplift modeling and evaluation library. Actively maintained pypi version.
sdpython/mlinsights
Extends scikit-learn with new models, transformers, metrics, plotting.
jseabold/statsmodels-tutorial
Tutorial Created for SciPy 2012
soerenkuenzel/causalToolbox
soerenkuenzel/forestry