Training PyTorch Models with data in your NoSQL Database

NoSQL Database

NoSQL databases are popular because they are highly scalable and flexible, making them ideal for handling large amounts of unstructured data. They can also be used to store structured data. NoSQL databases are designed to handle big data and can be used to store data in a variety of formats including JSON, XML, and BSON. They are also highly available and fault-tolerant. Additionally, they are designed to scale horizontally, allowing companies to add more computing power and storage as needed.

PyTorch Models

PyTorch is a machine learning framework based on the Torch library, used for applications such as computer vision and natural language processing. It was originally developed by Meta AI and now part of the Linux Foundation umbrella. PyTorch is designed to provide good flexibility and high speeds for deep neural network implementation. PyTorch uses dynamic computation graphs which makes it different from other deep learning frameworks. It has become a popular choice for deep learning tasks such as computer vision, natural language processing, and speech recognition. PyTorch has gained popularity for its simplicity, ease of use, dynamic computational graph, efficient memory usage, flexibility, speed, native ONNX model exports, which can be used to speed up inference. It also shares many commands with numpy which reduces the barrier to learning it.
With the growing popularity of both NoSQL databases for storage and PyTorch models for AI deployments, it is unsurprising that many organizations are seeking to train PyTorch models using data in their NoSQL database. Kaspian offers native connectors for the most popular NoSQL databases. Just register your NoSQL database as a datastore and link your model training job; Kaspian's autoscaling compute layer makes it easy to train and deploy PyTorch 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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