evidentlyai / evidently
Evidently is ββan 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.
β5,821Updated this week
Alternatives and similar repositories for evidently:
Users that are interested in evidently are comparing it to the libraries listed below
- ZenML π: The bridge between ML and Ops. https://zenml.io.β4,463Updated this week
- nannyml: post-deployment data science in pythonβ2,037Updated 2 months ago
- A curated list of awesome MLOps toolsβ4,359Updated 3 months ago
- Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML vaβ¦β3,731Updated last week
- Algorithms for outlier, adversarial and drift detectionβ2,318Updated last week
- An open-source data logging library for machine learning models and data pipelines. π Provides visibility into data quality & model perfβ¦β2,692Updated 2 months ago
- Learn how to design, develop, deploy and iterate on production-grade ML applications.β3,062Updated 6 months ago
- The fastest β‘οΈ way to build data pipelines. Develop iteratively, deploy anywhere. βοΈβ3,554Updated 5 months ago
- πΆ A tool to package, serve, and deploy any ML model on any platform. Archived to be resurrected one dayπ€β718Updated last year
- Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.β2,359Updated 2 months ago
- Feature engineering package with sklearn like functionalityβ2,008Updated last month
- Merlion: A Machine Learning Framework for Time Series Intelligenceβ4,209Updated 8 months ago
- The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!β7,469Updated this week
- The Open Source Feature Store for AI/MLβ5,866Updated this week
- π Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Modelsβ2,849Updated last month
- An end-to-end implementation of intent prediction with Metaflow and other cool toolsβ856Updated last year
- Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentationβ3,124Updated 2 months ago
- π Online machine learning in Pythonβ5,232Updated last week
- A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewβ¦β2,047Updated 5 months ago
- MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integraβ¦β1,497Updated this week
- βΎοΈ CML - Continuous Machine Learning | CI/CD for MLβ4,076Updated this week
- Lightning β‘οΈ fast forecasting with statistical and econometric models.β4,180Updated last week
- ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling β¦β5,864Updated this week
- Kickstart your MLOps initiative with a flexible, robust, and productive Python package.β1,179Updated this week
- Build, Deploy and Manage AI/ML Systemsβ8,619Updated this week
- A flexible, intuitive and fast forecasting libraryβ1,828Updated 3 weeks ago
- Algorithms for explaining machine learning modelsβ2,468Updated last week
- A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learningβ18,180Updated this week
- Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuniβ¦β3,112Updated 4 months ago
- Curated list of open source tooling for data-centric AI on unstructured data.β712Updated last year