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Machine learning library in Apache Spark
It is a scalable Machine learning library that discusses both high speed and high-quality algorithm.
To make machine learning scalable and easy, MLlib is created. There are machine learning libraries that included an implementation of various machine learning algorithms. For example, clustering, regression, classification and collaborative filtering. Some lower level machine learning primitives like generic gradient descent optimization algorithm are also present in MLlib.
In Apache Spark Version 2.0 the RDD-based API in spark. MLlib package entered in maintenance mode. In this release, the DataFrame-based API is the primary Machine Learning API for Spark.Therefore, MLlib will not add any new feature to the RDD based API.
DataFrame based API is that it is more user-friendly than RDD therefore MLlib is switching to DataFrame API. Some of the benefits of using DataFrames are it includes Spark Data sources, Spark SQL DataFrame queries Tungsten and Catalyst optimizations, and uniform APIs across languages. This Machine learning library also uses the linear algebra package Breeze. Breeze is a collection of libraries for numerical computing and machine learning.
To learn more about it, click on the link: Apache Spark MLlib (Machine Learning Library)
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