Training Computer Vision Models with MongoDB Data

MongoDB

MongoDB is a source-available cross-platform document-oriented database program. Classified as a NoSQL database program, MongoDB uses JSON-like documents with optional schemas. MongoDB has become one of the most wanted databases in the world because it makes it easy for developers to store, manage, and retrieve data when creating applications with most programming languages. MongoDB is popular because it's easy to learn and get started. It's highly scalable (auto-sharding) and cost-effective, and it has a flexible data model.

Computer Vision Models

Computer vision (CV) is a field of artificial intelligence (AI) that enables computers and systems to derive meaningful information from digital images, videos and other visual inputs and take actions or make recommendations based on that information. It trains convolutional neural networks to develop human-like vision capabilities for applications. Using digital images from cameras and videos and deep learning models, machines can accurately identify and classify objects and then react to what they see. Computer vision has many applications such as facial recognition, autonomous vehicles, medical imaging, robotics, surveillance, and more.
With the growing popularity of both MongoDB for storage and computer vision models for AI deployments, it is unsurprising that many organizations are seeking to train computer vision models using data in MongoDB. Kaspian offers native connectors for this operation. Just register your MongoDB datastore and link your model training job; Kaspian's autoscaling compute layer makes it easy to train and deploy computer vision models using any data in your cloud with minimal setup or management.
Learn more about Kaspian and see how our flexible compute layer for the modern data cloud is already reshaping the way companies in industries like retail, manufacturing and logistics are thinking about data engineering and analytics.

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