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

4.6
stars
13,545 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

SS

May 19, 2020

The course was very informative but I face a lot of problems in installing Graphlab and Turicreate. I request the Mentors please use the Pandas data frame in place of SFrame. The mentors are cool.

AH

Mar 28, 2022

very nice course.If you have basic knowledge of python datastructure then this course is best to start data science.All contents are beginner friendly which makes this course easily understandable.

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2751 - 2775 of 3,159 Reviews for Machine Learning Foundations: A Case Study Approach

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

By Alain C

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Feb 15, 2019

Technical setup is not easy, but great business cases.

By Mykhaylo K

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Oct 30, 2020

More practical approach and nothing theoretical (yet)

By SATYA P A

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Apr 29, 2020

its was very useful to learn about machine learning !

By rajeev r

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Oct 1, 2019

wonderful experience. It's like doing a live project.

By Abdulrahman M A K

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Jul 10, 2019

Awesome instructors and great knowledge and practices

By Divya v M

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May 29, 2016

Great overview and broad foundation of all techniques

By Jorge S N

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Apr 10, 2016

El más intuitivo curso de ML que he visto en Coursera

By HARSHIT J

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Jun 7, 2020

Average Course, don't have much expectations from it

By Bhakthavatsala R

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Jun 17, 2018

Interactive and very interesting. good for beginners

By Fenjin W

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Apr 16, 2016

Great course! Hope the slides gets better annotated.

By Prashant D

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Jun 16, 2020

The course was awesome and so does the Instructors!

By Yagyansh S K

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Dec 3, 2016

Awesome Teaching Technique Used! Kudos To The Team!

By Swechchha A

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Dec 17, 2022

i wished they taught using pandas scikit-learn too

By Mitali C

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Jun 10, 2020

It was Amazing course ,with amazing instructors :)

By Avinash P M

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Dec 14, 2016

Assignments could have been little more difficult.

By Alvin K

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Aug 17, 2020

Carlos and Emily are really cool. They're cool 😀

By Qing W

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Dec 6, 2017

didn't reach my expectation but still quite good.

By Albert Z

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Feb 7, 2016

Hands on should have been more involved/dificult.

By Omar H F A

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Jul 4, 2020

Very Good introductory course to the field of ML

By Gopinath T

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May 14, 2019

Well structured course with detailed explanation

By Sam P

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Jan 17, 2018

A bit light on details but a great first course!

By Qishen S

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May 26, 2017

A good overview of ML and tutorial for graphlab.