Statsmodels: statistical modeling and econometrics in Python
Collection of notebooks about quantitative finance, with interactive python code.
#计算机科学#Lightning ⚡️ fast forecasting with statistical and econometric models.
#计算机科学#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 goal...
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
#计算机科学#2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
#计算机科学#A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry throug...
#时序数据库#Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX ...
LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.
#学习与技能提升#This repository hosts the code behind the online book, Coding for Economists.
Causal Inference for the Brave and True的中文翻译版。全部代码基于Python，适用于计量经济学、量化社会学、策略评估等领域。英文版原作者：Matheus Facure
#时序数据库#Advanced and Fast Data Transformation in R
#时序数据库#Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.
Replication of tables and figures from "Mostly Harmless Econometrics" in Stata, R, Python and Julia.
#计算机科学#DoubleML - Double Machine Learning in Python
Visualise your CSV files in seconds without sending your data anywhere
📖An interactive companion to the well-received textbook 'Introduction to Econometrics' by Stock & Watson (2015)
