Scala Machine Learning Projects

Spark-based model deployment for large-scale dataset

In a production ready environment, we often need to deploy a pretrained models in scale. Especially, if we need to handle a massive amount of data. So our ML model has to face this scalability issue to perform continiously and with faster response. To overcome this issue, one of the main big data paradigms that Spark has brought for us is the introduction of in-memory computing (it supports dis based operation, though) and caching abstraction.

This makes Spark ideal for large-scale data processing and enables the computing nodes to perform multiple operations by accessing the same input data across multiple nodes in a computing cluster or cloud computing infrastructures (example, Amazon ...