Training Natural Language Processing 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.

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 NoSQL databases 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 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 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.