whylabs / whylogs
An open-source data logging library for machine learning models and data pipelines. π Provides visibility into data quality & model performance over time. π‘οΈ Supports privacy-preserving data collection, ensuring safety & robustness. π
β2,653Updated this week
Related projects β
Alternatives and complementary repositories for whylogs
- The fastest β‘οΈ way to build data pipelines. Develop iteratively, deploy anywhere. βοΈβ3,511Updated 2 months ago
- A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewβ¦β2,013Updated 2 months ago
- Evidently is ββan open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. Froβ¦β5,405Updated this week
- The Virtual Feature Store. Turn your existing data infrastructure into a feature store.β1,818Updated this week
- Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML vaβ¦β3,628Updated this week
- πΆ A tool to package, serve, and deploy any ML model on any platform. Archived to be resurrected one dayπ€β717Updated last year
- Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.ioβ1,913Updated last week
- Feathr β A scalable, unified data and AI engineering platform for enterpriseβ1,986Updated 7 months ago
- A light-weight, flexible, and expressive statistical data testing libraryβ3,401Updated this week
- An end-to-end implementation of intent prediction with Metaflow and other cool toolsβ847Updated last year
- The Open Source Feature Store for Machine Learningβ5,613Updated this week
- nannyml: post-deployment data science in pythonβ1,979Updated 2 weeks ago
- β704Updated 2 years ago
- Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.β3,309Updated last month
- ZenML π: The bridge between ML and Ops. https://zenml.io.β4,073Updated this week
- MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integraβ¦β1,446Updated this week
- Algorithms for outlier, adversarial and drift detectionβ2,249Updated this week
- Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadaβ¦β1,874Updated this week
- Scalable identity resolution, entity resolution, data mastering and deduplication using MLβ957Updated this week
- What's in your data? Extract schema, statistics and entities from datasetsβ1,434Updated last week
- Move fast from data science prototype to pipeline. Capture, analyze, and transform messy notebooks into data pipelines with just two lineβ¦β663Updated 6 months ago
- Python API for Deequβ730Updated last month
- A Python package to assess and improve fairness of machine learning models.β1,948Updated this week
- Monitor the stability of a Pandas or Spark dataframe βοΈβ497Updated last month
- π¦ Explore multimedia datasets at scaleβ1,042Updated last month
- The Fuzzy Labs guide to the universe of open source MLOpsβ449Updated 4 months ago
- ML pipeline orchestration and model deployments on Kubernetes.β435Updated last year
- Distributed data engine for Python/SQL designed for the cloud, powered by Rustβ2,336Updated this week
- Open-source low code data preparation library in python. Collect, clean and visualization your data in python with a few lines of code.β2,068Updated 4 months ago