Deepchecks Monitoring

Deepchecks Monitoring

Open Source Monitoring for AI & ML
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What do people think of Deepchecks Monitoring?

The community submitted 27 reviews to tell us what they like about Deepchecks Monitoring, what Deepchecks Monitoring can do better, and more.
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4.9/5All time (27 reviews)
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27 Reviews
Jonathan Harel

Founder & Leadership at Fine

6 reviews
Verified
I have been using Deepchecks for a while now, and I love that you guys keep it open source and keep improving it over time. Highly recommend this for data scientists: It's so simple to use and you get lots of value for free.
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Ohad Rozen
Entrepreneur
1 review
Amazing!!
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Marina Rudinsky
@marina_rudinsky1
1 review
Having had the privilege of contributing to Deepchecks' initial presentation design, I've witnessed first-hand the remarkable journey of this tool. Today, Deepchecks stands as a comprehensive solution for continuous ML validation, truly revolutionizing the field. The open-source core of Deepchecks offers an extensive suite of tools for testing and monitoring ML models. This functionality is invaluable to data scientists and ML engineers. The recent expansion to include both testing and monitoring is a testament to Deepchecks' commitment to meet the ever-evolving needs of the ML community. Deepchecks Hub is another impressive feature that deserves mention. It brings together the validation of multiple models in a managed and secure setting, accommodating everything from research to production. The hub's functionality includes scalable deployment options, the ability to validate multiple models in parallel, security and access management features, and support, making it a one-stop solution for commercial settings. From a product designer's perspective, I can't help but appreciate the intuitive user interface that Deepchecks has designed. The platform is easy to navigate with a logical layout that makes complex tasks feel manageable. The process of installing and setting up Deepchecks is refreshingly simple, requiring only a few lines of code. One of the standout features of Deepchecks is its broad support for different data types, including tabular data, computer vision, and NLP, throughout the model and data lifecycle. This flexibility makes it a versatile tool that can cater to a wide range of ML projects. Deepchecks' commitment to the open-source community is commendable. It fosters a collaborative environment that encourages continuous improvement and innovation. Regular updates, blog posts, and newsletters keep users informed about the latest industry trends, while the availability of a demo and comprehensive documentation make it easy for newcomers to get started. In conclusion, Deepchecks is an exceptional product that is transforming the landscape of ML validation. As someone who had a hand in its early stages, I am proud to see how far it has come and eagerly anticipate its future contributions to the field. I wholeheartedly recommend Deepchecks to anyone involved in machine learning, whether you're a seasoned data scientist, an ML engineer, or a newcomer to the field. This is a product that truly delivers on its promise, providing everything you need for continuous ML validation.
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Ido Kazma
Ido Kazma
@ido_kazma
1 review
Amazing tool. Easy to use and with immediate impact
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Lotan Levkowitz
Partner, Grove Ventures
2 reviews
Great product
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Ariel Biller
mod of r/mlops, come say hi on Twitter
2 reviews
I was waiting for their open-source offering! Can't wait to deploy this.
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Great product.
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Hagai Lalazar
@hagai_lalazar
2 reviews
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Ran Tavory
@ran_tavory1
1 review
Very useful for my day to day as DS
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Noam Cohen
@noam_cohen1
1 review
Love this product, saved us multiple times when doing research validation
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