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Deepchecks is the leading tool for testing and for validating your machine learning models and data, and it enables doing so with minimal effort. Deepchecks accompany you through various validation and testing needs such as verifying your data’s integrity, inspecting its distributions, validating data splits, evaluating your model and comparing between different models. While you’re in the research phase, and want to validate your data, find potential methodological problems, and/or validate...

...Covers the IAM family (KSI-IAM-MFA, KSI-IAM-APM, KSI-IAM-SNU, KSI-IAM-JIT, KSI-IAM-ELP, KSI-IAM-SUS, KSI-IAM-AAM) and MLA family (KSI-MLA-OSM, KSI-MLA-RVL, KSI-MLA-EVC, KSI-MLA-LET, KSI-MLA-ALA) in depth, with machine-readable YAML mappings, real AWS Config rule references, NIST 800-53 control crosswalks, and per-indicator evidence shapes that compliance engineers can use directly during 3PAO preparation. Includes the full FedRAMP machine-readable documentation (FRMR v0.9.43-beta) and a Python ksi-validator CLI for OSCAL package validation. Maintained by Boundera (https://boundera.io) as a community resource alongside the Boundera commercial product, which automates evidence collection across all 60 KSI indicators and 11 families on AWS, Azure, and GCP. MIT licensed.