Deepchecks
Shir Chorev is the Co-Founder and CTO of Deepchecks since 2019, where Shir leads the development of an innovative MLOps platform designed to evaluate AI and LLM-based applications, addressing issues such as hallucinations, toxicity, and PII leakage. Prior to this role, Shir served as the Machine Learning Research Leader at the Office of the Prime Minister of Israel from 2017 to 2019, focusing on AI/ML models for intelligence applications, and was the Product Team Lead at Israeli Military Intelligence from 2015 to 2017, overseeing complex technological projects. Shir began a career in cyber research within Israeli Military Intelligence's Unit 8200 from 2012 to 2015, and previously participated in the prestigious Talpiot Program from 2009 to 2012. Shir holds a Master's degree in Electrical and Computer Engineering from Tel Aviv University and a Bachelor's degree in Physics from The Hebrew University of Jerusalem.
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Deepchecks
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Build Test Suites for ML Models & Data with Deepchecks https://github.com/deepchecks/deepchecks Deepchecks is an open-source package for Machine Learning validation. Our Open Source is a python library for data scientists and ML engineers. The package includes extensive test suites for machine learning models and data, built in a way that’s flexible, extendable and editable. How Does It Work? Suites are composed of checks. Each check contains outputs to display in a notebook and/or conditions with a pass/fail output. - Conditions can be added or removed from a check; - Checks can be edited or added/removed to a suite; - Suites can be created from scratch or forked from an existing suite.