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Voltar para Machine Learning: Clustering & Retrieval

Comentários e feedback de alunos de Machine Learning: Clustering & Retrieval da instituição Universidade de Washington

4.7
estrelas
2,264 classificações
386 avaliações

Sobre o curso

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....

Melhores avaliações

JM
16 de Jan de 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.

BK
24 de Ago de 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.

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176 — 200 de 374 Avaliações para o Machine Learning: Clustering & Retrieval

por David F

21 de Out de 2016

Excellent course - and of great practical use.

por Nitish V

29 de Out de 2017

The Course is good . Covered lots of topics .

por Rahul G

13 de Jun de 2017

Good course but Week 5 LDA needs improvement.

por Stanislav B

15 de Abr de 2020

one of the best courses Ive seen on coursera

por Jason G

9 de Ago de 2017

Harder than the previous ones, but enjoyable

por Krisda L

19 de Jul de 2017

Good overview of a lot of useful techniques.

por felix a f a

8 de Ago de 2016

less complex exercises to check and validate

por Feiwen C ( C I

1 de Jun de 2017

Good course. Learned a lot from it. Thanks!

por Kan C Y

19 de Mar de 2017

Really a good course, succinct and concise.

por parag_verma

7 de Jan de 2020

Thanks to the entire team of this course.

por PRAVEEN R U

27 de Dez de 2018

Nice content and well made presentations.

por Miao J

1 de Jul de 2016

Another great course. Strongly recommend!

por Veer A S

23 de Mar de 2018

Very informative and interesting course.

por Ted T

29 de Jul de 2017

Best ML course ever. Easy to understand!

por Dmitri T

4 de Dez de 2016

Great course! Very simple and practical.

por Veera K R

6 de Abr de 2020

Very informative and Clearly explained.

por Snehotosh B

3 de Dez de 2016

Best course available till date as MooC

por kripa s

30 de Abr de 2019

One of the best training experience...

por Shuang D

29 de Jun de 2018

advanced knowledge on ML, great course

por Garvish

14 de Jun de 2017

Great Information and organised course

por RAJIT N

21 de Set de 2020

Everything was very clearly explained

por Ce J

26 de Jun de 2017

well organized and easy to understand

por 李紹弘

22 de Ago de 2017

This course provides concise course.

por Nada M

11 de Jun de 2017

Thank you! I loved all your classes.

por Fernando B

21 de Fev de 2017

Best Course on ML yet on the Web