Training Neural Network Models with Azure ABS Data

Azure ABS

Azure Data Lake Storage is primarily designed to work with Hadoop and all frameworks that use the Hadoop FileSystem as their data access layer (for example, Spark and Presto). It is a massively scalable, secure data lake functionality built on Azure Blob Storage which is designed for big data analytics and offers a hierarchical file system.

Neural Network Models

Neural networks are computing systems with interconnected nodes that work much like neurons in the human brain. They rely on training data to learn and improve their accuracy over time. Neural networks simulate how the brain learns by using multiple layers of nodes (input, hidden, and output) and they're able to learn both in supervised and unsupervised situations. They can recognize hidden patterns and correlations in raw data, cluster and classify it, and, over time, continuously learn and improve. Neural networks have many applications such as image recognition, speech recognition, natural language processing, autonomous vehicles, robotics, and more.

With the growing popularity of both Azure ABS for storage and neural network models for AI deployments, it is unsurprising that many organizations are seeking to train neural network models using data in Azure ABS. Kaspian offers native connectors for this operation. Just register your Azure ABS datastore and link your model training job; Kaspian's autoscaling compute layer makes it easy to train and deploy neural network 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.