Language model

As explained in Kafka for Architects

Inference is the generation of model predictions from input data using a trained machine-learning model.

A machine-learning model learns patterns from training data and uses them to predict values for new, unseen inputs. In live inference, it generates a prediction from a fresh event. section 12.4.1 section 12.4

Training can happen ahead of deployment: a model server hosts the trained model, while an application extracts event data, requests a prediction, and receives the result. Kafka can carry events into this flow and prediction results onward. section 12.4.1 section 12.4

A typical prediction flow separates model preparation from serving:

• Prepare data, define features and a target, then split the data for training and testing. section 12.4.1
• Train and evaluate the model, then deploy it to respond to new event data. section 12.4.1

Live prediction

An event can provide input for a fraud-detection prediction; the need for timely decisions makes streaming inference useful. section 12.4

Figure 12.6 The ML model is deployed in advance and is used by the Kafka Streams application for predictions.

Shows a previously deployed model being used by a Kafka Streams application to make predictions. section 12.4.1

How Kafka for Architects covers it

How deep it goes

Explains data preparation, train/test evaluation, and serving predictions, but stops short of algorithm internals.

Examples

Uses ad-click prediction and fraud detection to illustrate model targets and real-time inference.

What it assumes

Builds from zero through data cleaning, feature and target selection, and training and test splits.

What you can do after

Apply it via a deployed model server to produce predictions from incoming event data.

How it connects

Connects machine-learning models with Kafka, model servers, and incremental learning.

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Related concepts

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This explainer was generated by Manning's knowledge graph from the text of Kafka for Architects. The section links point to the parts of the book it draws on.