This repository provides a comprehensive list of resources for integrating Artificial Intelligence (AI) into Computer-Aided Engineering (CAE). It includes categorized tutorials, courses, research p…

A one stop repository for generative AI research updates, interview resources, notebooks and much more!

An evergrowing, professionally curated list of resources on everything decision-making: videos, tutorials, books, papers, theses, articles, datasets, and open-source libraries.

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

10 Weeks, 20 Lessons, Data Science for All!

12 Weeks, 24 Lessons, AI for All!

12 Weeks, 24 Lessons, IoT for All!

Applied Geodata Science book. Developed for the lecture(s) with the same name at the Institute of Geography, University of Bern.

counterfactuals: An R package for Counterfactual Explanation Methods

A Large-scale Benchmark Dataset for Data-Driven Streamflow Forecasting

Applied Deep Learning Course

This is the codebase for the paper - News-Based Sparse Machine Learning Models for Adaptive Asset Pricing - by Liao Zhu, Haoxuan Wu, and Martin T. Wells.

The multi-modal universe of fast-fashion: the Visuelle 2.0 benchmark

Time Series Cross-Validation

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo

Lightweight, useful implementation of conformal prediction on real data.

Python code for "Probabilistic Machine learning" book by Kevin Murphy

Data, Benchmarks, and methods submitted to the M5 forecasting competition

DoubleML - Double Machine Learning in R

"Probabilistic Machine Learning" - a book series by Kevin Murphy

The International Crisis Behavior Events (ICBe)

Bringing financial analysis to the tidyverse

Official Implementation of paper: Well Googled is Half Done: Multimodal Forecasting of New FashionProduct Sales with Image-based Google Trends

Datasets associated with pyprobml

A list of databases, datasets and books/handbooks where you can find materials properties for machine learning applications.

Analyse the FitBit Fitness Tracker Data to gain insights into how consumers and users are using the Fitbit App and discover trends.

Curated list for ML in FM

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels

🛠️ Corrected Test Sets for ImageNet, MNIST, CIFAR, Caltech-256, QuickDraw, IMDB, Amazon Reviews, 20News, and AudioSet