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

4.6
stars
13,494 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 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! 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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1801 - 1825 of 3,144 Reviews for Machine Learning Foundations: A Case Study Approach

By Neeti M

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Nov 1, 2020

good.. i like it...

By TEJAL H

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Jul 30, 2020

Fabulous instructor

By MALLAIAH V

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Jun 12, 2020

it is very helpfull

By Dimaz A P

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May 23, 2020

Best course so far!

By Magdi M

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Sep 11, 2018

Great case coverage

By nayan m

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Apr 6, 2018

Challenging and fun

By Yue

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Feb 24, 2018

Really great course

By Trinh N Q

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Jan 12, 2018

Great course so far

By Preetham G

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Nov 1, 2017

I loved this course

By Djibril N

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Jan 5, 2017

Complete and great.

By Georgios

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Oct 4, 2016

Absolutely amazing.

By Roger S

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Sep 4, 2016

This course is COOL

By ADESH T B M 2 B

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Apr 18, 2021

THANK YOU COURSERA

By Luis T

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Mar 25, 2021

Lovely experience.

By Shuchih N

•

Nov 4, 2020

QUITE good

😊😊😊😊

By rs

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Oct 22, 2020

Usefull to learing

By JAKKA S P S

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Oct 5, 2020

Its perfect course

By Sarthak S

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Aug 23, 2020

very nice and easy

By Diego L

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Aug 6, 2020

Excelente Curso!!!

By Harshita K

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Jul 14, 2020

Good for beginners

By Moe K O

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Jun 28, 2020

I love this course

By Nagarajapandian

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Jun 16, 2020

Very useful course

By IDOWU H A

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May 20, 2018

These Traininers a

By Jing

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Aug 14, 2017

Good for beginners

By Muhammad U

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Aug 11, 2017

Excellent Teaching