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

4.6
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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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2101 - 2125 of 3,140 Reviews for Machine Learning Foundations: A Case Study Approach

By mengheng x

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Jun 11, 2018

h很不错的入门课

By Shikha A

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May 6, 2018

Awesome!

By Aaryesh K

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Apr 5, 2018

too good

By 张业伟

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Sep 17, 2017

Perfect!

By Allen P

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May 19, 2017

awesome!

By 任晨熙

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Jan 28, 2017

很专业，正在学习

By Chaney C

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Nov 6, 2016

入门级别收获良多

By Việt N T H

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Aug 7, 2016

Awesome!

By Erickson M

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Jun 18, 2016

Excelent

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Oct 29, 2024

perfect

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Aug 10, 2024

amazing

By Souvik D

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Mar 30, 2021

awesome

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Nov 26, 2020

awesome

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Oct 28, 2020

Awesome

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Oct 12, 2020

Awesome

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Aug 27, 2020

AWESOME

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Aug 14, 2020

perfect

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May 16, 2020

Awesome

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May 7, 2020

Perfect

By Alicia_Qi

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Mar 2, 2018

Perfect

By Kuldeep K

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Aug 11, 2017

Amazing

By Navinkumar

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Feb 8, 2017

Its goo

By Pardeep S

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Nov 7, 2016

Awesome

By Jinho L

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Oct 11, 2016

Thanks!

By bardia a

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Apr 11, 2016

perfect