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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

4.6
2,163 個評分
371 條評論

課程概述

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....

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JM
2017年1月16日

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.

BK
2016年8月24日

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.

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151 - Machine Learning: Clustering & Retrieval 的 175 個評論(共 361 個)

創建者 Sameer M

2017年9月19日

Excellent course! must for machine learning beginners!!

創建者 陈佳艺

2017年5月17日

sometimes difficult,but import so many useful knowledge

創建者 백원광

2017年1月16日

Very sophisticated, friendly and practical instructions

創建者 Manoj K

2018年11月26日

session was very helpful & full with relevant contents

創建者 Siwei Y

2017年1月17日

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

2016年12月3日

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

創建者 KAI N

2019年1月3日

Excellent course with great and reachable explanation

創建者 Vladimir V

2017年6月27日

Awesome course. Thank you Emily, Carlos and Coursera!

創建者 Kishore P V

2016年10月5日

One of the best machine learning course I have taken.

創建者 Jaswant J

2017年3月31日

Very nice course. Concepts are covered very clearly.

創建者 Yang X

2017年11月14日

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

創建者 Sean L

2016年10月4日

wonderful course for beginner of machine learning.

創建者 Banka C G

2019年8月10日

Its my great experience for step by step modules

創建者 Yufeng X

2019年7月9日

It opened the door to more advanced techniques.

創建者 Anmol G

2016年12月16日

So Much Concepts to learn and totally worth it!

創建者 seokwon y

2018年7月26日

good to learn what is clustering and retrieval

創建者 Arash A

2017年1月5日

Enjoyed the course and learned a lot. Amazing!

創建者 David F

2016年10月21日

Excellent course - and of great practical use.

創建者 Nitish V

2017年10月29日

The Course is good . Covered lots of topics .

創建者 Rahul G

2017年6月13日

Good course but Week 5 LDA needs improvement.

創建者 Stanislav B

2020年4月15日

one of the best courses Ive seen on coursera

創建者 Jason G

2017年8月9日

Harder than the previous ones, but enjoyable

創建者 Krisda L

2017年7月19日

Good overview of a lot of useful techniques.

創建者 felix a f a

2016年8月8日

less complex exercises to check and validate

創建者 Feiwen C ( C I

2017年6月1日

Good course. Learned a lot from it. Thanks!