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Learner Reviews & Feedback for Machine Learning Foundations: A Case Study Approach by University of Washington

4.6
stars
13,527 ratings

About the Course

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....

Top reviews

BL

Oct 16, 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 19, 2016

Great course! Emily 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.

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2726 - 2750 of 3,156 Reviews for Machine Learning Foundations: A Case Study Approach

By paolo s

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Oct 5, 2016

It would be perfect if also cover a section on spark an mllib.

By Marco J

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Jan 14, 2022

Klasse Kurs, nur bei Graphlab vs. Turicreate etwas verwirrend

By yangxiaoqi

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Jan 29, 2018

可以在刚入门机器学习时候听一听这门课，能够知道机器学习在实际中如何应用的。但是要深入机器学习还是应当学学里面的数学知识的。

By Johan M

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Jun 9, 2016

Excellent course. Looking forward to the rest of the courses.

By David B

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Dec 4, 2015

A nice introduction to the various machine learning concepts.

By P V P

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Jun 28, 2020

its very basic just used a python module in the whole period

By SOWMYA P

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Jun 3, 2020

i understood many more in this course i understood properly.

By kumar p

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Oct 15, 2015

Nice for learners who want to jump start in machine learning

By Swapnil A

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Sep 6, 2020

Would have been a 5 start course if the content was updated

By R C

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Oct 9, 2020

A bit superficial, better to merge with following courses

By C M R

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Aug 4, 2020

VERY GOOD TEACHING AND GREAT INFORMATION IN THE LECTURES.

By krishna p

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Jun 24, 2016

This is very good material for machine learning starters.

By VJ

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Nov 16, 2015

good material. good presentation skills of the instructor

By Le D N

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Jul 11, 2021

Everything is good except the library used in Course ;(

By João G B A V

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Dec 4, 2017

Muito bom, os exemplos onlines poderiam ser interativos.

By Milan C

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Oct 20, 2017

Nice overview about different Machine Learning concepts.

By Jjclof

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Oct 17, 2016

Well-made.

Good teachers.

But a bit too simple. 4/5

Thanks.

By Markus M

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Feb 10, 2016

Good structure, but maybe a bit too basic and slow pace.

By Dai W

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Jan 3, 2016

I cannot review my completed homework. It's very boring.

By Lena M

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Dec 22, 2015

Loved the course, the teachers, the case study approach.

By DARSHI A

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Jul 12, 2020

It is a good course and proffesors are explaining cool.

By Andy L

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Aug 4, 2017

Good introduction. Don't expect more than that though.

By Wangjun

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Dec 29, 2016

This course is very good.Thankyou for all the teachers.

By SUHARIKA V

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Nov 26, 2021

the experiance is good and assignments are interesting

By TAMATAM V S P R

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Aug 11, 2020

The course about machine learning is awesome.

thank you