Based on our record, AWS DeepLens should be more popular than Evidently AI. It has been mentiond 5 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
AWS provides various services for Machine Learning and Artificial Intelligence, including Amazon SageMaker, AWS DeepLens, AWS DeepComposer, Amazon Forecast and more. Familiarize yourself with the services available to determine which ones suit your specific needs. - Source: dev.to / 4 months ago
Take a look at AWS deeplens. You might be able to make something work out of it. https://aws.amazon.com/deeplens/. Source: over 1 year ago
AWS DeepLens - Deep learning enabled video camera for developers - AWS (amazon.com). - Source: dev.to / about 2 years ago
So Amazon has this thing called Deep Lens. Https://aws.amazon.com/deeplens/ Basically, it's a really dinky computer with all the things needed to do Machine Learning with image recognition. It comes with several projects that all are about how to program it, and how to run machine learning enabled image recognition projects (including 'Hotdog-Not A Hotdog'!). It's an expense, but it would enable what you're... Source: over 2 years ago
AWS DeepLens is a hardware offering from AWS. It comes with a fully programmable camera you can use to train Machine Learning models for your specific task. Tutorials and guides also accompany this to get started right away. - Source: dev.to / about 3 years ago
It is doable. However the main focus of MLFlow is in experiment tracking. I would suggest for you to look into another monitoring tools such evidentlyai . You can track more things than performance (e.g.data drift). Which may be helpful in a production setting. Source: almost 2 years ago
Evidently is an open-source Python library that analyzes and monitors machine learning models. It generates interactive reports based on Panda DataFrames and CSV files for troubleshooting models and checking data integrity. These reports show model health, data drift, target drift, data integrity, feature analysis, and performance by segment. - Source: dev.to / over 2 years ago
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