Chevron Left
Zurück zu Machine Learning: Clustering & Retrieval

Bewertung und Feedback des Lernenden für Machine Learning: Clustering & Retrieval von University of Washington

2,315 Bewertungen

Über den Kurs

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....



24. Aug. 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.


16. Jan. 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.

Filtern nach:

151 - 175 von 383 Bewertungen für Machine Learning: Clustering & Retrieval

von Shaonan W

20. Nov. 2016

Deep insight into most useful techniques of machine learning.

von JOSE R

18. Nov. 2017

Very well explained. The LDA was difficult to learn. Thanks.

von Daniel R

16. Aug. 2016

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

von Yifei L

30. Juli 2016

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

von Victor C

24. Juni 2017

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

von Guillermo O d A

4. Juni 2022

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

von Francisco R M

19. März 2021

Too many assingments dedicated to on scratch development.

von Moayyad Y

4. Dez. 2016

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

von Fengchen G

2. Sep. 2016

Awesome course! The session on EM algorithm is revealing!

von Divyang S

13. Sep. 2020

Excellent content... Really intuitive and well explained

von Yong D K

7. Mai 2018

This is the best course for Information Retrieval ever!

von Sameer M

19. Sep. 2017

Excellent course! must for machine learning beginners!!

von 陈佳艺

17. Mai 2017

sometimes difficult,but import so many useful knowledge

von Joseph P

16. Jan. 2017

Very sophisticated, friendly and practical instructions

von Manoj K

26. Nov. 2018

session was very helpful & full with relevant contents

von Siwei Y

17. Jan. 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。

von Oleg B

3. Dez. 2016

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

von Niu K

3. Jan. 2019

Excellent course with great and reachable explanation

von Vladimir V

27. Juni 2017

Awesome course. Thank you Emily, Carlos and Coursera!

von Kishore P V

5. Okt. 2016

One of the best machine learning course I have taken.

von Jaswant J

31. März 2017

Very nice course. Concepts are covered very clearly.

von Yang X

14. Nov. 2017

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

von Sean L

4. Okt. 2016

wonderful course for beginner of machine learning.

von Banka C G

10. Aug. 2019

Its my great experience for step by step modules

von Yufeng X

9. Juli 2019

It opened the door to more advanced techniques.