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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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13,492 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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By bardia a

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Apr 11, 2016

perfect

By stephen

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Jan 8, 2016

awesome

By Priyank P

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Dec 2, 2015

awesome

By Emilio C Q

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Oct 1, 2015

Uber!!!

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Oct 8, 2023

,,,,,,

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Aug 22, 2023

superb

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Nov 28, 2020

arumai

By Anshumaan K P

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Nov 4, 2020

nYc :)

By W.A.P.C. S

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May 24, 2020

Great!

By Nithya B

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Mar 15, 2018

useful

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Dec 17, 2017

Great!

By sandeep

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May 29, 2017

Thanks

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Nov 4, 2024

Круто

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Oct 14, 2024

Круто

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Oct 7, 2024

жаксы

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May 30, 2023

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Oct 9, 2020

great

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Jun 25, 2020

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Jun 12, 2020

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By MOSTAFA E A M

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Mar 1, 2020

Great