What is Map and Reduce in Machine Learning?

What is Map and Reduce in Machine Learning?

Map and Reduce are programming models used for processing large data sets with a distributed algorithm on a cluster.

Can you explain how the Map function works?

The Map function takes a dataset and applies a specified function to each element, producing a new dataset.

And what about the Reduce function?

The Reduce function takes the output from the Map function and combines it to produce a smaller, summarized dataset.

How are these concepts applied in real-world machine learning?

They are used in tasks like data preprocessing, feature extraction, and aggregating results from distributed computations.