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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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13,545 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

RM

Feb 3, 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.

RH

Jun 9, 2017

I felt this course did a good job introducing the student to Machine Learning. The examples and hands on assignments brought the concepts home. I was able to use the knowledge immediately at work.

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By Palwasha G

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Sep 26, 2019

BEST

By Wu C

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Jul 1, 2018

good

By Xuewei C

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Jan 8, 2018

帮助很大

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Nov 27, 2017

good

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Apr 13, 2017

good

By Yu-Jhen-Wu

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Jan 9, 2017

Nice

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Jan 6, 2016

good

By Esteban A

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Sep 25, 2015

FUN!

By SAI V K

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Aug 28, 2020

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By Vansh S

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May 11, 2019

nic

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NC

By Stephen G

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Jan 15, 2021

NA

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Sep 11, 2020

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By Douba J

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May 29, 2020

bn

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Apr 27, 2020

ok

By Magdiel A

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May 7, 2019

Ok

By SongMyungjin

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Oct 12, 2017

ok

By Younghwan K

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Dec 24, 2016

Ex

By Alexander A S G

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Dec 26, 2015

ok

By Naman G

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Jul 18, 2025

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Nov 27, 2020

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Oct 23, 2020

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By kyasa P

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Jul 11, 2020

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