Training Natural Language Processing Models with data in your Data Lake

Data Lake

Data lakes are popular because they provide a consolidated, centralized storage area for raw, unstructured, semi-structured, and structured data taken from multiple sources and lacking a predefined schema. They specialize in ingesting structured, semi-structured and unstructured data and provide mechanisms to easily ingest streaming data in addition to batch loads. Data lakes are open format so users avoid lock-in to a proprietary system like a data warehouse. They are also highly durable and low cost because of their ability to scale and leverage object storage.

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 data lakes 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 data lake. Kaspian offers native connectors for the most popular data lakes. Just register your data lake 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.