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워싱턴 대학교의 Machine Learning Foundations: A Case Study Approach 학습자 리뷰 및 피드백

4.6
9,047개의 평가
2,162개의 리뷰

강좌 소개

Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems? In this course, you will get hands-on experience with machine learning from a series of practical case-studies. At the end of the first course you will have studied how to predict house prices based on house-level features, analyze sentiment from user reviews, retrieve documents of interest, recommend products, and search for images. Through hands-on practice with these use cases, you will be able to apply machine learning methods in a wide range of domains. This first course treats the machine learning method as a black box. Using this abstraction, you will focus on understanding tasks of interest, matching these tasks to machine learning tools, and assessing the quality of the output. In subsequent courses, you will delve into the components of this black box by examining models and algorithms. Together, these pieces form the machine learning pipeline, which you will use in developing intelligent applications. Learning Outcomes: By the end of this course, you will be able to: -Identify potential applications of machine learning in practice. -Describe the core differences in analyses enabled by regression, classification, and clustering. -Select the appropriate machine learning task for a potential application. -Apply regression, classification, clustering, retrieval, recommender systems, and deep learning. -Represent your data as features to serve as input to machine learning models. -Assess the model quality in terms of relevant error metrics for each task. -Utilize a dataset to fit a model to analyze new data. -Build an end-to-end application that uses machine learning at its core. -Implement these techniques in Python....

최상위 리뷰

BL

Oct 17, 2016

Very good overview of ML. The GraphLab api wasn't that bad, and also it was very wise of the instructors to allow the use of other ML packages. Overall i enjoyed it very much and also leaned very much

SZ

Dec 20, 2016

Great course!\n\nEmily and Carlos teach this class in a very interest way. They try to let student understand machine learning by some case study. That worked well on me. I like this course very much.

필터링 기준:

Machine Learning Foundations: A Case Study Approach의 2,081개 리뷰 중 251~275

교육 기관: carloswhite

Mar 17, 2018

it is nice

교육 기관: A.Gamal

May 11, 2018

A very Good Introductory course to begin your machine learning journey

교육 기관: Ganghee J

Dec 02, 2016

Great introduction to the machine learning!

교육 기관: Francisco P

Jun 25, 2017

Thanks to the teachers, they prepared exciting, complete and interesting clases. The course is very useful to understand the main areas in machine learning. Totally recommended!

교육 기관: Radwa E S

Apr 26, 2018

The course introduces most of the basis of machine learning in a very simple and clear way illustrated by real world examples

교육 기관: Matthew T

Dec 30, 2016

Really interesting material thought very enthusiastically. Enjoyed it loads

교육 기관: dilu583

Apr 12, 2017

good

교육 기관: Paul M

Feb 04, 2018

I like the case study approach. Much easier and more relevant way to learn the topic.

교육 기관: Srividya N

Nov 01, 2017

There is so much of flexibility. It is so cool and so interesting... I could complete this complex course so easily with some of the key activities like below:

Exercise videos

taking quiz questions multiple times with no penalty

simple English and explanation of complex information in simple and easy terms

교육 기관: 吴晗

Aug 23, 2017

I've learned a lot about machine learning and graphlab, many thanks.

교육 기관: zoom

Mar 05, 2018

good ,It is very useful for me

교육 기관: Mattheüs d K

Jun 13, 2018

Brilliant course with the best imaginable teachers!

교육 기관: Rodrigo T

Sep 06, 2017

Excelent Course, nice examples.

교육 기관: stephon_lu

Nov 08, 2017

the course is great!

교육 기관: Raymond C

Oct 16, 2016

Solid overview of the various ML techniques without getting too far into the math behind it.

교육 기관: Vincent L

Aug 18, 2016

Excellent Course!

교육 기관: Seo J

Sep 13, 2017

G

교육 기관: KUMAR K

Oct 30, 2016

A wonderful foundation course on Machine Learning to understand its various facets... !!!

교육 기관: Brian S

Sep 27, 2017

Loved the case study approach and how it relates to real world problems. Utilizing graphlab also helped abstract away a lot of the details, but I look forward to diving deeper with the rest of the specializations!

교육 기관: Anatoly M

Apr 16, 2017

Great introduction to machine learning, not too much math but gives a good idea of what ML is + gives practice in Python (which was my initial goal).

The tests contained a few inaccuracies (they didn't completely match on my machine/setup), but otherwise was fine.

교육 기관: byeongwook.seo

Oct 27, 2017

Great Lecture!

교육 기관: Samuel d Z

Jun 17, 2017

Great Course, so much valuable information and in combination with Python/Graphlab, I think it is perfect when starting out on ML. Looking forward to the other 3 courses in this series. Lectures are both perfect and tempo is exactly as needed.

교육 기관: Harshitha C

May 01, 2017

A very comprehensive course taught in a very easy and interesting manner!

교육 기관: muhammad r k k

Jan 09, 2018

Amazing course on Machine Learning.I have tried other courses on Machine Learning but none has made it so simple for me as this course.I started other courses but at some point I was stuck but this course explains all concepts so easily and gradually .Highly recommended for anyone who want to start learning machine learning.Even if you do not have programming experience, its easy to follow.

I congratulate both the instructors Emily and Carlos for making this brilliant course.

My most favorite part of this course is when Emily is trying to pronounce the name "Pele" and Carlos corrects here lol.

교육 기관: Ida C

Jun 06, 2017

This course is interesting, it is good for someone know nothing about machine learning.