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

4.6
stars
13,544 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 18, 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.

RM

Feb 2, 2022

I was very disappointed with the exclusion of the final courses and the capstone project. The most interesting part of specialization no longer exists and no plausible justification has been given.

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2101 - 2125 of 3,159 Reviews for Machine Learning Foundations: A Case Study Approach

By 于飞飞

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May 14, 2016

very good

By Xinwei L

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May 2, 2016

very cool

By Pradeep M

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Apr 4, 2016

Excellent

By Maxwell N M

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Dec 12, 2015

Very Cool

By Giovanni C A

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Nov 2, 2015

Excellent

By Zhenis A

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Oct 22, 2024

Огонь!!!

By Gaurav P

•

Apr 26, 2023

3700Rs/-

By Ayoub I

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May 17, 2022

good job

By Mustefa A U

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Dec 19, 2020

good job

By Malèk R

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Oct 11, 2020

Good job

By mahantesh k

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Sep 24, 2020

excelent

By S. M S H

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Sep 4, 2020

Good one

By Md. T U B

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Jul 10, 2020

excelent

By GIRISH S

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Jun 27, 2020

nice one

By Steve F S

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Apr 27, 2020

awesome!

By mengheng x

•

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 4, 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 6, 2016

Awesome!

By Erickson M

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Jun 18, 2016

Excelent

By Haider A

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Apr 9, 2025

amzaing