English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper presents Deepchecks, a Python library for comprehensivelyvalidating machine learning models and data. Our goal is to provide aneasy-to-use library comprising of many checks related to various types ofissues, such as model predictive performance, data integrity, data distributionmismatches, and more. The package is distributed under the GNU Affero GeneralPublic License (AGPL) and relies on core libraries from the scientific Pythonecosystem: scikit-learn, PyTorch, NumPy, pandas, and SciPy. Source code,documentation, examples, and an extensive user guide can be found at\url{https://github.com/deepchecks/deepchecks} and\url{https://docs.deepchecks.com/}.

Deepchecks: A Library for Testing and Validating Machine Learning Models and Data