MasaAsami

MasaAsami's Stars

• microsoft/ML-For-Beginners

  12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

  Language:HTML70.3k1k13614.8k

• OpenBB-finance/OpenBB

  Investment Research for Everyone, Everywhere.

  Language:Python34.7k2882.2k3.2k

• freqtrade/freqtrade

  Free, open source crypto trading bot

  Language:Python33.5k6784.9k6.7k

• satellite-image-deep-learning/techniques

  Techniques for deep learning with satellite & aerial imagery

  8.9k279241.5k

• nebuly-ai/optimate

  A collection of libraries to optimise AI model performances

  Language:Python8.4k93202637

• dair-ai/ML-Papers-Explained

  Explanation to key concepts in ML

  7.4k1528581

• 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.

  Language:Python7.2k140482937

• evidentlyai/evidently

  Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

  Language:Jupyter Notebook5.6k48409614

• paulgp/applied-methods-phd

  Repo for Yale Applied Empirical Methods PHD Course

  Language:HTML2k744590

• jrfiedler/causal_inference_python_code

  Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins

  Language:Jupyter Notebook1.3k522390

• pymc-labs/CausalPy

  A Python package for causal inference in quasi-experimental settings

  Language:Python9352222465

• matteocourthoud/awesome-causal-inference

  A curated list of causal inference libraries, resources, and applications.

  894411150

• PacktPublishing/Causal-Inference-and-Discovery-in-Python

  Causal Inference and Discovery in Python by Packt Publishing

  Language:Jupyter Notebook8111911275

• BiomedSciAI/causallib

  A Python package for modular causal inference analysis and model evaluations

  Language:Python743232199

• fulifeng/Causal_Reading_Group

  We will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NUS) and LDS (USTC) by week.

  50835478

• pybotters/pybotters

  An advanced API client for python bot traderes.

  Language:Python3981616077

• sibylhe/mmm_stan

  Python/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROAS

  Language:Jupyter Notebook3621215165

• matheusfacure/causal-inference-in-python-code

  Code for the Book Causal Inference in Python

  Language:Jupyter Notebook27474122

• msuzen/looper

  A resource list for causality in statistics, data science and physics

  257133634

• ondra-novak/mmbot

  Market Making trading bot for cryptomarkets

  Language:C++231263558

• microsoft/showwhy

  Language:TypeScript209123627

• BennyThadikaran/stock-pattern

  A Python CLI tool to scan, detect, and plot stock chart patterns

  Language:Python196111341

• hakuhodo-technologies/scope-rl

  SCOPE-RL: A python library for offline reinforcement learning, off-policy evaluation, and selection

  Language:Python1185911

• bernardodionisi/differences

  difference-in-differences in Python

  Language:Python9551820

• nathanwang000/Shapley-Flow

  Language:Jupyter Notebook50526

• drillan/mkdeco-jquants-api-option

  Language:Jupyter Notebook12202

• kazuyanagimoto/staggered_did_tutorial

  2023年5月28日に日本経済学会春季大会にて開催されたチュートリアル・セッション（共催：日本学術会議 数量的経済・政策分析分科会）「DIDの計量経済手法の近年の展開」のサポートサイトとしてスライド資料（講義編・演習基礎編・演習応用編）、Stataコード、Rコードを提供しています．

  Language:R12192

• drillan/mkdeco-hackathon-lt

  マケデコハッカソン LT大会 presented by J-Quants

  Language:Jupyter Notebook10302

• xiaomanluo/ripwPaper

  Paper repository for "Double Robust Two-Way Fixed Effect Regression for Panel Data"

  Language:R10107

• Dingseewhole/Robust_Deconfounder_master

  Language:Python8213