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

4.6
stars
13,492 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.

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

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951 - 975 of 3,143 Reviews for Machine Learning Foundations: A Case Study Approach

By Oliver W

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May 3, 2016

Absolutely love the light hearted approach and am having a great time learning something I love.

By Rajib M

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Mar 14, 2016

SFrame & GraphLab tutorials were great, Really liked how it was presented .

Loving this Course !

By Poonam H

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Jul 18, 2020

It was a very helpful course. I got to learn many new things and also I learnt a new subject .

By Mohit C

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Mar 5, 2019

The idea on the teaching method by taking case study was a great choice. Great work keep it up.

By Leandro D

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Sep 7, 2017

Excelent approach on the case study, looking forward to the next projects of the specialization

By Mukul P

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Dec 7, 2016

Exceptional introduction to all of the concepts involving Machine Learning! Highly Recommended!

By Eduardo D

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Aug 31, 2016

It is a well organized and motivating introduction to the incredible field of Machine Learning.

By Alfredo A M S

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Jun 26, 2016

Good overview of ML methods combined with a gentle introductions to Python and iPython notebook

By David T

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Mar 31, 2022

Is a perfect course to learn ML foundations, all explanations are clear and easy to undestand.

By Aldo M

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Nov 9, 2020

Es un curso profesional, los profesores son dedicados y carismáticos te aseguro que aprenderás

By Hardik K

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May 5, 2019

Excellent course, the way it was taught was awesome, and i am in love with machine learning...

By Sankar B

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Apr 21, 2019

Awesome...Brilliant lectures... So lucid... But initially struggled to setup the environment.

By Justin L

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Aug 30, 2018

The course is very practical and contributes to the understanding of machine learning theory.

By Ramzy K

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Jun 17, 2017

Lovely course, and lovely instructors, and THANK YOU for the financial aid, i love Coursera ♥

By Ross H

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Mar 5, 2017

Well structured and engaging.

Quality videos, good pacing. Tools were interesting to work with

By Mark M

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Oct 22, 2016

It was a great course and had good hands on materials. Now for the theoretical underpinnings!

By Adrián M

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Feb 8, 2016

Great teachers. Great presentations. Great way to learn Machine Learning. Highly recommended.

By Debajyoti D

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Jun 27, 2020

Excellent course , and specially the guides were very helpful, just awesome in one sentence.

By Ankit A

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Jun 17, 2020

Amazing course. Fun instructors. Loved the depth of details. Apt for an introductory course.

By Lagadic A

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Nov 24, 2019

Great course to get a big picture of what machine learning is, what the models involved are.

By Ashutosh R C

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Mar 24, 2018

good course for a beginner. I am already getting some amazing ideas on some practical usage.

By Ravi c

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Sep 16, 2017

Amazing Course...This course will set a very strong foundation for your data science career.

By Simon F

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Aug 8, 2017

Great overview over use cases in regression, classification and product recommender systems.

By Cheng Z

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Aug 6, 2017

The courses are really great for any starter to understand the fundamental knowledge of ML.

By C. G F

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Jan 11, 2017

General introduction to machine learning approaches and their application in real scenarios.