Top Tools To Do Machine Learning Serving In Production

Creating a model is one thing, but using that model in production is quite another. The next step after a data scientist completes a model is to deploy it so that it can serve the application. Batch and online model serving are the two main categories. Batch refers to feeding a large amount of data into a model and writing the results to a table, usually as a scheduled operation. You must deploy the model online using an endpoint for applications to send a request to the model and receive a quick response with no latency.