Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through R&D-Agent, which lets AI drive data-driven AI. πhttps://aka.ms/RD-Agent-Tech-Report
A unified framework for machine learning with time series
A Python library for anomaly detection across tabular, time series, graph, text, image, and audio data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.
π :bar_chart: :bulb: Orange: Interactive data analysis
A library of extension and helper modules for Python's data analysis and machine learning libraries.
STUMPY is a powerful and scalable Python library for modern time series analysis
Python library and CLI for X/Twitter scraping with multi-account rotation and built-in rate-limit handling.
Extract structured data from PDF invoices
A Python toolkit/library for reality-centric machine/deep learning & data mining on partially-observed time series, with 50+ SOTA neural network models for scientific analysis tasks (imputation, classification, clustering, forecasting, anomaly detection, cleaning) on incomplete industrial irregularly-sampled multivariate TS with NaN missing values
Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)
A Deep Learning Python Toolkit for Healthcare Applications.
Multi-class confusion matrix library in Python
UnityPy is python module that makes it possible to extract/unpack and edit Unity assets
A toolkit for time series machine learning and deep learning
AIL framework - Analysis Information Leak framework. Project moved to https://github.com/ail-project
Official public repository for PM4Py (Process Mining for Python) β an open-source library for exploring, analyzing, and optimizing business processes with Python.
AIL framework - Analysis Information Leak framework
[IEEE T-KDE 2026] Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).