chaiyunhai's Stars
quixio/quix-streams
Python stream processing for Kafka
Nixtla/statsforecast
Lightning ⚡️ fast forecasting with statistical and econometric models.
GoogleCloudPlatform/ml-design-patterns
Source code accompanying O'Reilly book: Machine Learning Design Patterns
stitchfix/hamilton
A scalable general purpose micro-framework for defining dataflows. THIS REPOSITORY HAS BEEN MOVED TO www.github.com/dagworks-inc/hamilton
EthicalML/awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
annoviko/pyclustering
pyclustering is a Python, C++ data mining library.
visenger/awesome-mlops
A curated list of references for MLOps
rlabbe/Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
trekhleb/learn-python
📚 Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.
MaxBenChrist/awesome_time_series_in_python
This curated list contains python packages for time series analysis
mattharrison/ml_pocket_reference
Resources for Machine Learning Pocket Reference
nndl/nndl.github.io
《神经网络与深度学习》 邱锡鹏著 Neural Network and Deep Learning
d2l-ai/d2l-zh
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
Atcold/NYU-DLSP20
NYU Deep Learning Spring 2020
bharathgs/Awesome-pytorch-list
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
lmoroney/dlaicourse
Notebooks for learning deep learning
facebook/prophet
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
PracticalTimeSeriesAnalysis/BookRepo
SmirkCao/Lihang
Statistical learning methods, 统计学习方法(第2版)[李航] [笔记, 代码, notebook, 参考文献, Errata, lihang]
xnie/rlearner
Quasi-Oracle Estimation of Heterogeneous Treatment Effects
yuuwill/1024app-android
草榴官方客户端，小草客户端，Android
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.
rguo12/awesome-causality-algorithms
An index of algorithms for learning causality with data
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.
Minyus/causallift
CausalLift: Python package for causality-based Uplift Modeling in real-world business
Yimeng-Zhang/feature-engineering-and-feature-selection
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
DistrictDataLabs/yellowbrick
Visual analysis and diagnostic tools to facilitate machine learning model selection.
shap/shap
A game theoretic approach to explain the output of any machine learning model.
datawhalechina/pumpkin-book
《机器学习》（西瓜书）公式详解
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