Cluster analysis is the task of grouping objects together based on their similarity to each other. It is used in various fields such as pattern recognition, image analysis, and bioinformatics. There are different algorithms and parameters that can be used to achieve clustering, and it is an iterative process that involves trial and error.

Stanford University

Spring 2023

This course focuses on data mining and machine learning algorithms for large scale data analysis. The emphasis is on parallel algorithms with tools like MapReduce and Spark. Topics include frequent itemsets, locality sensitive hashing, clustering, link analysis, and large-scale supervised machine learning. Familiarity with Java, Python, basic probability theory, linear algebra, and algorithmic analysis is required.

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+ 17 more conceptsPrinceton University

Fall 2017

A thorough introduction to machine learning principles such as online learning, decision making, gradient-based learning, and empirical risk minimization. It also explores regression, classification, dimensionality reduction, ensemble methods, neural networks, and deep learning. The course material is self-contained and based on freely available resources.

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