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The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.
Open-source data movement for ELT pipelines and AI agents — from APIs, databases & files to warehouses, lakes, and AI applications. Both self-hosted and Cloud.
Turns Data and AI algorithms into production-ready web applications in no time.
An orchestration platform for the development, production, and observation of data assets.
The Data Engineering Cookbook
macOS development environment setup: Easy-to-understand instructions with automated setup scripts for developer tools like Vim, Sublime Text, Bash, iTerm, Python data analysis, Spark, Hadoop MapReduce, AWS, Heroku, JavaScript web development, Android development, common data stores, and dev-based OS X defaults.
:truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
MLBox is a powerful Automated Machine Learning python library.
pyspark methods to enhance developer productivity 📣 👯 🎉
The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.
Engine for AI/ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.
Streaming reactive and dataflow graphs in Python
amqplib fork
Build and deploy a serverless data pipeline on AWS with no effort.
Helpers & syntactic sugar for PySpark.
Stream Processing Made Easy
Reverse ETL for the code-first data stack
Declarative data quality engine. Define checks in YAML, run anywhere.
A detective for your data. Zero-config data quality monitoring — works with dbt, Postgres, BigQuery, Snowflake. No YAML.