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

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

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

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

Automatic extraction of relevant features from time series:

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

Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft

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 go…

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

Source code accompanying O'Reilly book: Machine Learning Design Patterns

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

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

Causal Inference and Discovery in Python by Packt Publishing

Serverless Machine Learning Course for building AI-enabled Prediction Services from models and features

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

Code for the Book Causal Inference in Python

An intuitive library to extract features from time series. To cite this software publication: https://www.sciencedirect.com/science/article/pii/S2352711020300017

Curated Python Notebooks for Amazing Data Visualization

게임 데이터를 통해 인과관계를 추론하는 능력을 향상시킬 수 있는 책입니다.

End-to-end ML workflow to highlight SageMaker Feature Store