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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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826 - 850 of 3,156 Reviews for Machine Learning Foundations: A Case Study Approach

By ANDREAS M

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Dec 24, 2021

It was absolutely stunning! I loved the way was presented and i will definitely look forward to continue on this path

By Mohamed H

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Sep 1, 2020

Great course, I have learned many things about machine learning and I plan to go on the specialization.

Thanks so much.

By Dhanesh A

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Oct 27, 2016

At high level it gives glimpse of different machine learning domains. One can then decide to go deep into one of them.

By SeptemberHX

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Sep 19, 2016

An overview about machine learning. After finishing it, you can get some important structures about ml.

Keep learning.

By Ian W

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Jun 16, 2016

Great class! I loved the case study approach. I am looking foreword to digging into the details in the next classes.

By Brajendra G

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Apr 3, 2016

Excellent Course. Just loved it. Both Prof. Carlos and Prof. Emily has done a fantastic job. Thank you for everything.

By John

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Mar 16, 2016

very good introductory course. It presents the outline of Machine Learning with concrete examples. Highly recommended!

By Andreas H

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Feb 9, 2022

It was a very fruitful and amazing experience to take part in this "Case Study Approach". Thanks to Emily and Carlos!

By Hong C

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Jun 14, 2017

Introduce and explain different ideas in Machine Learning clearly and logically! I've learned a lot from this course!

By Raj

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Jun 2, 2017

Provides a very good foundation for the subsequent specialization courses on classification, regression & clustering.

By Norman Y

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Apr 24, 2018

Good beginning course. Week 6 could use more explanations and clearer examples. Somewhat difficult in the examples.

By Varun R

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Sep 23, 2017

The professors are really fun and the case study methodology to teach the concepts of machine learning was superb. !

By yiliang z

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Feb 18, 2016

Interesting approach, clear and organized structure, well prepared contents and up-to-date implementation techniques

By Juan C A

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Jan 4, 2016

Great broad overview of ML. Found the use of ipython notebooks very useful and the use of graphlab very interesting.

By Guruprasad N

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Dec 25, 2020

Really appreciated the after course exercises, they are simple but still very effective. I really liked them a lot.

By Sri M K S

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May 13, 2020

Explained with real time problems and examples , Explanation is very good, i gained good knowledge from this course

By Joseph F

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Mar 12, 2018

a very good start with cases of machine learning, think more tutorial with pandas and sklearn could be much better.

By 郑蔡云

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Nov 29, 2017

many tools and practical methods are introduced. It would undoubtedly be a pleasant experience to take this course.

By Vinod T G

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Aug 14, 2017

Excellent course for folks who need to understand ML and how it can be used in an array of day to day applications

By Anderson d S

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Jul 24, 2016

The course is really awesome. Of all the introductory Machine Learning courses I've taken, this is one is the best!

By Mohd A

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Feb 6, 2016

Specialization is very well organized. A very good intro. to ML followed by rigorous details in subsequent courses.

By 叶国桥

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Jan 10, 2016

There are so many good cases to help you understanding the basic concept about machine learning.

I would learn more!

By Jayavarapu D | A

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Jun 23, 2021

I personally need appreciate a lot. This is so helpful to me to solve all the case studies and some real problems.

By Md. R H M

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Apr 28, 2020

I really loved the Quiz sections. I had the feeling that I am doing something and not just watching the stuffs on.

By Srinivas C

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Apr 30, 2018

This course was really amazing. I got to learn a lot of new things. required to kick start advanced courses in ML.