intellygenta

moment

MOMENT: A Family of Open Time-series Foundation Models

timesfm

TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.

aeon

A toolkit for machine learning from time series

giskard

🐢 Open-Source Evaluation & Testing for LLMs and ML models

soda-core

:zap: Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io

pandera

A light-weight, flexible, and expressive statistical data testing library

whylogs

An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈

deepchecks

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

DataProfiler

What's in your data? Extract schema, statistics and entities from datasets

great_expectations

Always know what to expect from your data.

TabPFN

Official implementation of the TabPFN paper (https://arxiv.org/abs/2207.01848) and the tabpfn package.

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.

DeepClustering

Methods and Implements of Deep Clustering

dinov2

PyTorch code and models for the DINOv2 self-supervised learning method.

nnenum

Neural Network Enumeration Tool

netron

Visualizer for neural network, deep learning and machine learning models

alpha-beta-CROWN

alpha-beta-CROWN: An Efficient, Scalable and GPU Accelerated Neural Network Verifier (winner of VNN-COMP 2021, 2022, and 2023)

NeuralVerification.jl

Methods to soundly verify deep neural networks

rocket

ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels

aimlflow

aim-mlflow integration

upgini

Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & commercial LLMs

DeepTime

PyTorch code for Learning Deep Time-index Models for Time Series Forecasting (ICML 2023)

datasetsforecast

Datasets for time series forecasting

LaST

Code for paper titled "Learning Latent Seasonal-Trend Representations for Time Series Forecasting" in NeurIPS 2022

flow-forecast

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

nbeatsx

statsforecast

Lightning ⚡️ fast forecasting with statistical and econometric models.

spacetimeformer

Multivariate Time Series Forecasting with efficient Transformers. Code for the paper "Long-Range Transformers for Dynamic Spatiotemporal Forecasting."

LTSF-Linear

[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"

libmaxdiv

Implementation of the Maximally Divergent Intervals algorithm for Anomaly Detection in multivariate spatio-temporal time-series.