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Machine Learning: Clustering & Retrieval に戻る

ワシントン大学(University of Washington) による Machine Learning: Clustering & Retrieval の受講者のレビューおよびフィードバック



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....



Jan 17, 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.


Aug 25, 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.


Machine Learning: Clustering & Retrieval: 151 - 175 / 326 レビュー

by Yang X

Nov 15, 2017

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

by Sean L

Oct 04, 2016

wonderful course for beginner of machine learning.

by Banka C G

Aug 10, 2019

Its my great experience for step by step modules

by Yufeng X

Jul 09, 2019

It opened the door to more advanced techniques.

by Anmol G

Dec 16, 2016

So Much Concepts to learn and totally worth it!

by yoon s w

Jul 26, 2018

good to learn what is clustering and retrieval

by Arash A

Jan 05, 2017

Enjoyed the course and learned a lot. Amazing!

by David F

Oct 21, 2016

Excellent course - and of great practical use.

by Nitish V

Oct 29, 2017

The Course is good . Covered lots of topics .

by Rahul G

Jun 13, 2017

Good course but Week 5 LDA needs improvement.

by Stanislav B

Apr 15, 2020

one of the best courses Ive seen on coursera

by Jason G

Aug 09, 2017

Harder than the previous ones, but enjoyable

by Krisda L

Jul 19, 2017

Good overview of a lot of useful techniques.

by felix a f a

Aug 08, 2016

less complex exercises to check and validate

by Feiwen C ( C I

Jun 02, 2017

Good course. Learned a lot from it. Thanks!

by Kan C Y

Mar 19, 2017

Really a good course, succinct and concise.

by parag_verma

Jan 07, 2020

Thanks to the entire team of this course.


Dec 27, 2018

Nice content and well made presentations.

by Miao J

Jul 01, 2016

Another great course. Strongly recommend!

by Veer A S

Mar 24, 2018

Very informative and interesting course.

by Ted T

Jul 29, 2017

Best ML course ever. Easy to understand!

by Dmitri T

Dec 05, 2016

Great course! Very simple and practical.

by Veera K R

Apr 06, 2020

Very informative and Clearly explained.

by Snehotosh K B

Dec 03, 2016

Best course available till date as MooC

by kripa s

Apr 30, 2019

One of the best training experience...