Machine Learning: Clustering & Retrieval

Start Date: 11/03/2019

Course Type: Common Course

Course Link: https://www.coursera.org/learn/ml-clustering-and-retrieval

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Course Syllabus

Clustering and retrieval are some of the most high-impact machine learning tools out there. Retrieval is used in almost every applications and device we interact with, like in providing a set of products related to one a shopper is currently considering, or a list of people you might want to connect with on a social media platform. Clustering can be used to aid retrieval, but is a more broadly useful tool for automatically discovering structure in data, like uncovering groups of similar patients.

This introduction to the course provides you with an overview of the topics we will cover and the background knowledge and resources we assume you have.

Deep Learning Specialization on Coursera

Course Introduction

In this course, you will also examine structured representations for describing the documents in the corpus, including clustering and mixed membership models, such as latent Dirichlet allocation (LDA). You will implement expectation maximization (EM) to learn the document clusterings, and see how to scale the methods using MapReduce.

Course Tag

Machine Learning Clustering Retrieval Machine Learning Model Clustering Model Retrieval Model LDA Document Similarity Data Clustering Algorithms K-Means Clustering K-D Tree

Related Wiki Topic

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