Chevron Left
返回到 Machine Learning: Clustering & Retrieval

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

4.6
1,777 個評分
305 個審閱

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....

熱門審閱

BK

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.

JM

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.

篩選依據:

76 - Machine Learning: Clustering & Retrieval 的 100 個評論(共 293 個)

創建者 Jinho L

Sep 20, 2016

Great! thanks

創建者 Pradeep N

Feb 22, 2017

"super one,

創建者 Manuel I C M

Aug 15, 2017

Excellent Course!

創建者 Stephen G

Aug 14, 2016

Yet another really excellent course in this series - the best online course I have ever taken. I really appreciate the fairly high level on which it is taught, and the speed with which they go through the material - it is not here to entertain or waste time, but to get straight to the point - what can I do, and how do I use open source tools to do it?

創建者 Yifei L

Jul 30, 2016

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

創建者 felix a f a

Aug 08, 2016

less complex exercises to check and validate

創建者 Abhilash V

Feb 20, 2017

A great course as the other 3 courses in the specialization.This course introduces and make us implement Knn,Kd trees,Gaussian Mixture model and LDA model for clustering and retrieval.The data set is the peoples wiki from the Foundations course and theres a assignment on clustering images too.If you have taken the other 3 an do this with ease and if you haven't taken those i think it will be better to take this course after the other 3.

創建者 Edward F

Jun 25, 2017

I took the 4 (formerly 6) courses that comprised this certification, so I'm going to provide the same review for all of them.

This course and the specialization are fantastic. The subject matter is very interesting, at least to me, and the professors are excellent, conveying what could be considered advanced material in a very down-to-Earth way. The tools they provide to examine the material are useful and they stretch you out just far enough.

My only regret/negative is that they were unable to complete the full syllabus promised for this specialization, which included recommender systems and deep learning. I hope they get to do that some day.

創建者 Ridhwanul H

Oct 17, 2017

Like all the other ones, this as well was an amazing course. The topics covered in were the most interesting ones till now for me, as earlier days when I started programming I used often think about problems like these and used to wonder how it was done. Now I feel like I might be able to do them.

Its a shame that you no longer provide the Recommender System course, since that was something I was even more interested in, and its kinda sad that I am not gonna have access to it.

創建者 Jaswant J

Mar 31, 2017

Very nice course. Concepts are covered very clearly.

創建者 RISHABH T

Nov 12, 2017

excellent

創建者 Christopher D

Aug 09, 2016

Superb course!

創建者 Rohan K

Mar 22, 2018

Good introduction to very complicated concepts. I now have the tools to learn more about HHMs and anomaly detection.

創建者 MARC G

Oct 21, 2017

Clear and well designed course. The assignments are quite thorough. Sometimes, quiz question are not so clear though.

創建者 Roger S

Sep 04, 2016

Worth the wait. COOL learning

創建者 Kuntal G

Nov 03, 2016

Very Good in depth explanation and hand-on lab machine learning course. very focused on real world analytics and algorithms

創建者 Robi s

Sep 18, 2017

Great instruction, great course, and provide information I used directly in my work.

創建者 Arash A

Jan 05, 2017

Enjoyed the course and learned a lot. Amazing!

創建者 Kishore P V

Oct 05, 2016

One of the best machine learning course I have taken.

創建者 Sandeep J

Sep 04, 2016

Best course I've taken!! :)

創建者 Michael B

Jul 12, 2016

Not for the faint of heart but this course does a really good job of explaining clustering (and retrieval) of images and text. It includes several programming assignments which can be tackled with minimal programming experience if one perseveres.

創建者 Diogo J A P

Jan 25, 2017

The material is complex and challenging, but the teaching procedure is carefully thought out in a way that you quickly get it, giving you a great sense of accomplishment.

創建者 Rama K R N R G

Sep 09, 2017

Good presentation of topics. Detailed walk through of few advanced topics covered at the end would have been great. Felt the presentation went too fast.

創建者 Renato R S

Aug 27, 2016

A perfect and balanced introduction to the subjects, adding theory and practice beautifully.

創建者 Andrey N

Mar 12, 2017

Some themes are shown very superficially it would be great to go deeper. Despite of this the course is great!

Thanks.