๐ฆพ MLOps
Open source platform for the machine learning lifecycle
Open Source ML Model Versioning, Metadata, and Experiment Management
do more with dbt. dbt-fal helps you run Python alongside dbt, so you can send Slack alerts, detect anomalies and build machine learning models.
Evidently is โโan 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.
The fastest โก๏ธ way to build data pipelines. Develop iteratively, deploy anywhere. โ๏ธ
๐ Material for PyData Global 2021 Presentation: Effective Testing for Machine Learning Projects
โพ๏ธ CML - Continuous Machine Learning | CI/CD for ML
The Fuzzy Labs guide to the universe of open source MLOps
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine
Build and share delightful machine learning apps, all in Python. ๐ Star to support our work!
Create powerful Hydra applications without the yaml files and boilerplate code.
Hydra is a framework for elegantly configuring complex applications
nannyml: post-deployment data science in python
๐ค Evaluate: A library for easily evaluating machine learning models and datasets.
A scalable general purpose micro-framework for defining dataflows. THIS REPOSITORY HAS BEEN MOVED TO www.github.com/dagworks-inc/hamilton
PySpark test helper methods with beautiful error messages
pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (โฆ
Prefect is a workflow orchestration framework for building resilient data pipelines in Python.
Turns Data and AI algorithms into production-ready web applications in no time.
Lightning fast data version control system for structured and unstructured machine learning datasets. We aim to make versioning datasets as easy as versioning code.
Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
Utils for streaming large files (S3, HDFS, gzip, bz2...)
๐ข๐๐ป ๐ฌ๐ผ๐๐ฟ ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ. Skore's open-source Python library accelerates ML model development with automated evaluation reports, smart methodological guidance, and comprehensive cross-validation analyโฆ
Uncomplicated Observability for Python and beyond! ๐ชต๐ฅ
Cost-efficient and pluggable Infrastructure components for GenAI inference
A high-throughput and memory-efficient inference and serving engine for LLMs