deepchecks
uncertainty-toolbox
Our great sponsors
deepchecks | uncertainty-toolbox | |
---|---|---|
15 | 1 | |
3,350 | 1,711 | |
2.8% | 3.1% | |
8.2 | 10.0 | |
8 days ago | over 1 year ago | |
Python | Python | |
GNU General Public License v3.0 or later | MIT License |
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.
deepchecks
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Detect, Defend, Prevail: Payments Fraud Detection using ML & Deepchecks
Also if you have any confusion related to it. You can directly go to their discussion section in github :
- Deepchecks: Open-source ML testing and validation library
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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.
- Deepchecks
- deepchecks: Test Suites for Validating ML Models & Data. Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort.
- QA help comes in many forms: Sometimes, from your heavily funded competitor
- Deepchecks: An open-source tool for testing machine learning models and data
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Test suites for machine learning models in Python (New OSS package)
And if you liked the project, we'll be delighted to count you as one of our stargazers at https://github.com/deepchecks/deepchecks/stargazers!
uncertainty-toolbox
What are some alternatives?
great_expectations - Always know what to expect from your data.
cleverhans - An adversarial example library for constructing attacks, building defenses, and benchmarking both
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
TorchDrift - Drift Detection for your PyTorch Models
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.
pytea - PyTea: PyTorch Tensor shape error analyzer
feast - Feature Store for Machine Learning
backpack - BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.
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.
uq-vae - Solving Bayesian Inverse Problems via Variational Autoencoders
giskard - 🐢 Open-Source Evaluation & Testing framework for LLMs and ML models
ipme - An interactive visualization tool that transforms probabilistic programming models into an "Interactive Probabilistic Models Explorer".