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Learner Reviews & Feedback for Machine Learning: Clustering & Retrieval by University of Washington

4.7
stars
2,357 ratings

About the Course

Case Studies: Finding Similar Documents A reader is interested in a specific news article and you want to find similar articles to recommend. What is the right notion of similarity? Moreover, what if there are millions of other documents? Each time you want to a retrieve a new document, do you need to search through all other documents? How do you group similar documents together? How do you discover new, emerging topics that the documents cover? In this third case study, finding similar documents, you will examine similarity-based algorithms for retrieval. 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. Learning Outcomes: By the end of this course, you will be able to: -Create a document retrieval system using k-nearest neighbors. -Identify various similarity metrics for text data. -Reduce computations in k-nearest neighbor search by using KD-trees. -Produce approximate nearest neighbors using locality sensitive hashing. -Compare and contrast supervised and unsupervised learning tasks. -Cluster documents by topic using k-means. -Describe how to parallelize k-means using MapReduce. -Examine probabilistic clustering approaches using mixtures models. -Fit a mixture of Gaussian model using expectation maximization (EM). -Perform mixed membership modeling using latent Dirichlet allocation (LDA). -Describe the steps of a Gibbs sampler and how to use its output to draw inferences. -Compare and contrast initialization techniques for non-convex optimization objectives. -Implement these techniques in Python....

Top reviews

BK

Aug 24, 2016

excellent material! It would be nice, however, to mention some reading material, books or articles, for those interested in the details and the theories behind the concepts presented in the course.

JM

Jan 16, 2017

Excellent course, well thought out lectures and problem sets. The programming assignments offer an appropriate amount of guidance that allows the students to work through the material on their own.

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151 - 175 of 389 Reviews for Machine Learning: Clustering & Retrieval

By Shaonan W

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Nov 20, 2016

Deep insight into most useful techniques of machine learning.

By JOSE R

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Nov 18, 2017

Very well explained. The LDA was difficult to learn. Thanks.

By Daniel R

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Aug 16, 2016

Another great hit by Emily and Carlos!!! Excellent Course!!!

By Yifei L

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Jul 30, 2016

Good course for KD trees, LSH, Gaussian mixed model and LDA.

By Victor C

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Jun 24, 2017

Excellent teacher and material. I wish there were more...

By Guillermo O d A

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Jun 4, 2022

Excellent course. I am looking forward for a second part.

By Francisco R M

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Mar 19, 2021

Too many assingments dedicated to on scratch development.

By Moayyad Y

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Dec 4, 2016

this is not a an easy course but certainly an awesome one

By Fengchen G

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Sep 2, 2016

Awesome course! The session on EM algorithm is revealing!

By Divyang S

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Sep 13, 2020

Excellent content... Really intuitive and well explained

By Yong D K

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May 7, 2018

This is the best course for Information Retrieval ever!

By Sameer M

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Sep 19, 2017

Excellent course! must for machine learning beginners!!

By 陈佳艺

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May 17, 2017

sometimes difficult,but import so many useful knowledge

By Joseph P

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Jan 16, 2017

Very sophisticated, friendly and practical instructions

By Manoj K

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Nov 26, 2018

session was very helpful & full with relevant contents

By Siwei Y

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Jan 17, 2017

本来不报什么期望，但是该门课确实做得相当好。　相信该课的老师们花了巨大的心血。真的是业界良心。所以强烈点赞。

By Oleg B

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Dec 3, 2016

Great course, very hands-on, very practical knowledge.

By Niu K

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Jan 3, 2019

Excellent course with great and reachable explanation

By Vladimir V

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Jun 27, 2017

Awesome course. Thank you Emily, Carlos and Coursera!

By Kishore P V R

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Oct 5, 2016

One of the best machine learning course I have taken.

By Jaswant J

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Mar 31, 2017

Very nice course. Concepts are covered very clearly.

By Yang X

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Nov 14, 2017

Thank you Emily and Carlos! You guys are amazing!!!

By Sean L

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Oct 4, 2016

wonderful course for beginner of machine learning.

By Banka C G

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Aug 10, 2019

Its my great experience for step by step modules

By Yufeng X

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Jul 9, 2019

It opened the door to more advanced techniques.