Build better models with
Predictive models are only as good as the data that powers them. Anovos is an open-source project designed for data scientists who want to better understand their data and create features that result in high performing machine learning models.
- Analyze and profile your data and features
- Low code detection and correction of quality issues and anomalies
- Identifying optimum features
- Mapping data to features
- Custom feature creation
Bringing it All Together with Anovos
You want to create an ML pipeline that leads to building high performing models. Anovos unifies the key methods necessary to more easily understand your data and create the most predictive, stable features.
With robust analytics, in-depth analysis and comprehensive metrics, Anovos helps you better understand your data, and through feature recommendation and transformation build more resilient models.
Anovos also has unique features such as a scalable data stability calculation, giving your entire team insight into which data may shift over time and impact model accuracy and performance. And a feature recommender to address the cold start problem getting you off to the right start in choosing the most stable features.
Anovos has multiple editions designed to meet the needs of the individual data scientist as well as data science teams working with enterprise scale data sets.
- Designed for an individual data scientist or analyst
- Supports data sets up to 5GB
- Distributed processing to support enterprise scale data sets
Frequently Asked Questions
While we are continuing to build on Anovos and expand its capabilities, today, Anovos can help you better understand your data by providing you with out of the box, comprehensive analytics and metrics and can help you transform your data into features that will power resilient models. Go ahead, give it a try.