Training Natural Language Processing 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.

Natural Language Processing Models

Natural language processing (NLP) refers to the branch of computer science, and more specifically, the branch of artificial intelligence or AI-concerned with giving computers the ability to understand text and spoken words in much the same way human beings can. NLP combines computational linguistics-rule-based modeling of human language with statistical machine learning algorithms. NLP has been used in many applications such as chatbots, sentiment analysis, speech recognition, machine translation, and more.

With the growing popularity of both MongoDB for storage and natural language processing models for AI deployments, it is unsurprising that many organizations are seeking to train natural language processing 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 natural language processing 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.