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Machine Learning: Clustering & Retrieval(으)로 돌아가기

워싱턴 대학교의 Machine Learning: Clustering & Retrieval 학습자 리뷰 및 피드백

4.6
별점
2,299개의 평가

강좌 소개

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....

최상위 리뷰

BK

2016년 8월 24일

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

2017년 1월 16일

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.

필터링 기준:

Machine Learning: Clustering & Retrieval의 381개 리뷰 중 151~175

교육 기관: Daniel R

2016년 8월 16일

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

교육 기관: Yifei L

2016년 7월 30일

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

교육 기관: Victor C

2017년 6월 24일

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

교육 기관: Guillermo O d A

2022년 6월 4일

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

교육 기관: Francisco R M

2021년 3월 19일

Too many assingments dedicated to on scratch development.

교육 기관: Moayyad Y

2016년 12월 4일

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

교육 기관: Lawrence G

2016년 9월 2일

Awesome course! The session on EM algorithm is revealing!

교육 기관: Divyang S

2020년 9월 13일

Excellent content... Really intuitive and well explained

교육 기관: Yong D K

2018년 5월 7일

This is the best course for Information Retrieval ever!

교육 기관: Sameer M

2017년 9월 19일

Excellent course! must for machine learning beginners!!

교육 기관: 陈佳艺

2017년 5월 17일

sometimes difficult,but import so many useful knowledge

교육 기관: Joseph P

2017년 1월 16일

Very sophisticated, friendly and practical instructions

교육 기관: Manoj K

2018년 11월 26일

session was very helpful & full with relevant contents

교육 기관: Siwei Y

2017년 1월 17일

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。

교육 기관: Oleg B

2016년 12월 3일

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

교육 기관: Niu K

2019년 1월 3일

Excellent course with great and reachable explanation

교육 기관: Vladimir V

2017년 6월 27일

Awesome course. Thank you Emily, Carlos and Coursera!

교육 기관: Kishore P V

2016년 10월 5일

One of the best machine learning course I have taken.

교육 기관: Jaswant J

2017년 3월 31일

Very nice course. Concepts are covered very clearly.

교육 기관: Yang X

2017년 11월 14일

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

교육 기관: Sean L

2016년 10월 4일

wonderful course for beginner of machine learning.

교육 기관: Banka C G

2019년 8월 10일

Its my great experience for step by step modules

교육 기관: Yufeng X

2019년 7월 9일

It opened the door to more advanced techniques.

교육 기관: Anmol g

2016년 12월 16일

So Much Concepts to learn and totally worth it!

교육 기관: seokwon y

2018년 7월 26일

good to learn what is clustering and retrieval