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

4.6
stars
13,485 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

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.

PM

Aug 18, 2019

The course was well designed and delivered by all the trainers with the help of case study and great examples.

The forums and discussions were really useful and helpful while doing the assignments.

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801 - 825 of 3,140 Reviews for Machine Learning Foundations: A Case Study Approach

By prativa a

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Nov 14, 2020

Very good approach.. i is really easy to understand when we can learn on the basis of real world. So i like this course.

By Duke

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Apr 4, 2020

Basic introduction and the test is really time-cost. But with careful guidance and nice professor, I rate it as 5 stars!

By Aakash S

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May 25, 2019

One of the best in the business covering all the basics in a very concise and understandable way. Thanks a lot Coursera.

By Fahad S

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Nov 2, 2018

The case study approach works perfectly to enhance motivation. It sets up the stage for diving deep into the algorithms.

By Robin G

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Jan 10, 2017

Le cours utilise la pédagogie par projet ! Ce qui est la meilleure approche à mes yeux. Fortement conseillé aux novices.

By Akash S

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Aug 7, 2016

An excellent introductory course. Unlike other courses, demonstrations are really good and matter is concise & relevant.

By KRISHNA K Y

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Jun 23, 2016

excellent overview of the ML and to the point, enough to start head on into the subject without beating around the bush.

By Junkai Z

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Apr 23, 2016

A very good and precise review for all the application of popular machine learning algorithms, provide great intuitions.

By Iain M

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Mar 25, 2016

A well-structured and well taught introduction to the subject, I feel fully prepared for the next course in the series.

By Angel S

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Nov 6, 2015

Great course and excellent hands-on introduction to ML techniques.

Looking forward to next courses in the specialization.

By Andres V T (

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Feb 22, 2024

pretty useful and great course. The scope of the course is broad and so well explained, without making it overwhelming.

By Akash T

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Jun 8, 2020

This will be my first machine learning course.I am very happy to be here and learn new things and different algorithms.

By Carlos M d l S

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Jul 3, 2018

Well-structured course built around specific problems and how to solve them using Machine Learning. Highly recommended.

By 陈弘毅

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Jan 8, 2018

the course is pretty and interesting, i was excited to learn all the material in the lecture with the guide of mentors

By Noufal S

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Apr 21, 2016

It's a little hard but i suppose it is meant to be hard because i am studying the hottest course in the world right now

By Fokhruz Z

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Feb 28, 2016

Case Study Based Approach is VERY important in learning new technologies. Need some more practical Capstone Projects...

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!