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學生對 华盛顿大学 提供的 Machine Learning: Clustering & Retrieval 的評價和反饋

2,125 個評分
368 條評論


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.


151 - Machine Learning: Clustering & Retrieval 的 175 個評論(共 356 個)

創建者 Manoj K

Nov 26, 2018

session was very helpful & full with relevant contents

創建者 Siwei Y

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。

創建者 Oleg B

Dec 04, 2016

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

創建者 KAI N

Jan 03, 2019

Excellent course with great and reachable explanation

創建者 Vladimir V

Jun 27, 2017

Awesome course. Thank you Emily, Carlos and Coursera!

創建者 Kishore P V

Oct 05, 2016

One of the best machine learning course I have taken.

創建者 Jaswant J

Mar 31, 2017

Very nice course. Concepts are covered very clearly.

創建者 Yang X

Nov 15, 2017

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

創建者 Sean L

Oct 04, 2016

wonderful course for beginner of machine learning.

創建者 Banka C G

Aug 10, 2019

Its my great experience for step by step modules

創建者 Yufeng X

Jul 09, 2019

It opened the door to more advanced techniques.

創建者 Anmol G

Dec 16, 2016

So Much Concepts to learn and totally worth it!

創建者 seokwon y

Jul 26, 2018

good to learn what is clustering and retrieval

創建者 Arash A

Jan 05, 2017

Enjoyed the course and learned a lot. Amazing!

創建者 David F

Oct 21, 2016

Excellent course - and of great practical use.

創建者 Nitish V

Oct 29, 2017

The Course is good . Covered lots of topics .

創建者 Rahul G

Jun 13, 2017

Good course but Week 5 LDA needs improvement.

創建者 Stanislav B

Apr 15, 2020

one of the best courses Ive seen on coursera

創建者 Jason G

Aug 09, 2017

Harder than the previous ones, but enjoyable

創建者 Krisda L

Jul 19, 2017

Good overview of a lot of useful techniques.

創建者 felix a f a

Aug 08, 2016

less complex exercises to check and validate

創建者 Feiwen C ( C I

Jun 02, 2017

Good course. Learned a lot from it. Thanks!

創建者 Kan C Y

Mar 19, 2017

Really a good course, succinct and concise.

創建者 parag_verma

Jan 07, 2020

Thanks to the entire team of this course.


Dec 27, 2018

Nice content and well made presentations.