The official Python library for the Google Gemini API

21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

Documentation for Google's Gen AI site - including the Gemini API and Gemma

Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI

Dara is a dynamic application framework designed for creating interactive web apps with ease, all in pure Python.

Causal Inference and Discovery in Python by Packt Publishing

게임 데이터를 통해 인과관계를 추론하는 능력을 향상시킬 수 있는 책입니다.

Code for the Book Causal Inference in Python

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.

Causal Inference for The Brave and True 책의 한국어 번역 자료입니다.

Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

A python library for user-friendly forecasting and anomaly detection on time series.

This curated list contains python packages for time series analysis

Curated Python Notebooks for Amazing Data Visualization

Official Notion JavaScript Client

The library for web and native user interfaces.

This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop at Neural Information Processing Systems (NeurIPS) 2020.

A Python library that helps data scientists to infer causation rather than observing correlation.

🧱 Databricks CLI eXtensions - aka dbx is a CLI tool for development and advanced Databricks workflows management.

A Machine Learning library based on Theano

Code and hyperparameters for the paper "Generative Adversarial Networks"

Uplift modeling and causal inference with machine learning algorithms

Kernel CI Test for Relational Data (Lee and Honavar, UAI 2017), which accounts relational structure induced heterogeneity

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

A game theoretic approach to explain the output of any machine learning model.

Open-source low code data preparation library in python. Collect, clean and visualization your data in python with a few lines of code.

Automated data-centric processing

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 graphic…

Data Efficient Decision Making