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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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2076 - 2100 of 3,140 Reviews for Machine Learning Foundations: A Case Study Approach

By jorge j l c

Sep 5, 2018

Excelente

By blues星星

Aug 17, 2018

m满分,讲的很不错

By 肖攀

Dec 18, 2017

很满意,因为有中文

By Sérgio E L

Oct 30, 2017

Excellent

By Deleted A

Sep 10, 2017

very good

By divas v

May 2, 2017

Excellent

By fan c

Mar 20, 2017

深入浅出,通俗易懂

By Jake G

Dec 6, 2016

Loved it!

By threefish

Aug 30, 2016

very good

By Rajiv B

Aug 21, 2016

Loved it.

By 于飞飞

May 14, 2016

very good

By Xinwei L

May 2, 2016

very cool

By Pradeep M

Apr 5, 2016

Excellent

By Maxwell N M

Dec 12, 2015

Very Cool

By Giovanni C A

Nov 3, 2015

Excellent

By Zhenis A

Oct 22, 2024

Огонь!!!

By Gaurav P

Apr 27, 2023

3700Rs/-

By Ayoub I

May 17, 2022

good job

By Mustefa A U

Dec 20, 2020

good job

By Malèk R

Oct 11, 2020

Good job

By mahantesh k

Sep 25, 2020

excelent

By S. M S H

Sep 4, 2020

Good one

By Md. T U B

Jul 10, 2020

excelent

By GIRISH S

Jun 27, 2020

nice one

By Steve F S

Apr 28, 2020

awesome!