explainerdashboard
deepchecks
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explainerdashboard | deepchecks | |
---|---|---|
2 | 15 | |
2,172 | 3,295 | |
- | 2.7% | |
8.0 | 8.6 | |
11 days ago | 6 days ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
explainerdashboard
deepchecks
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Deepchecks' New Open Source is on Product Hunt, and Needs Your Help
GitHub for Deepchecks: https://github.com/deepchecks/deepchecks
- [D] DL Practitioners, Do You Use Layer Visualization Tools s.a GradCam in Your Process?
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Data Validation tools
I use DeepChecks for my continuous training pipelines. You can check out the Data Integrity Checks.
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How to trust your machine learning model with Deepchecks
Deepchecks (https://github.com/deepchecks/deepchecks) is an open-source Python package for comprehensively validating your machine learning models and data with minimal effort. This includes checks related to various types of issues, such as model performance, data integrity, distribution mismatches, and more.
Explore the docs https://docs.deepchecks.com
- [P] Deepchecks: an open-source tool for high standards validations for ML models and data.
What are some alternatives?
great_expectations - Always know what to expect from your data.
model-validation-toolkit - Model Validation Toolkit is a collection of tools to assist with validating machine learning models prior to deploying them to production and monitoring them after deployment to production.
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
feast - Feature Store for Machine Learning
postgresml - The GPU-powered AI application database. Get your app to market faster using the simplicity of SQL and the latest NLP, ML + LLM models.
giskard - 🐢 Evaluation & Testing framework for LLMs and ML models
Activeloop Hub - Data Lake for Deep Learning. Build, manage, query, version, & visualize datasets. Stream data real-time to PyTorch/TensorFlow. https://activeloop.ai [Moved to: https://github.com/activeloopai/deeplake]
polyaxon - MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
cleverhans - An adversarial example library for constructing attacks, building defenses, and benchmarking both
flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
shapash - 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!