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

4.6
stars
13,531 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 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.

RH

Jun 8, 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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2126 - 2150 of 3,157 Reviews for Machine Learning Foundations: A Case Study Approach

By Souvik D

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Mar 30, 2021

awesome

By Manisha B

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Nov 26, 2020

awesome

By Swayambrata M

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Oct 28, 2020

Awesome

By Ibrahim K

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Oct 12, 2020

Awesome

By Joy B

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Aug 27, 2020

AWESOME

By Teymurlu K

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Aug 14, 2020

perfect

By Ovi S

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May 16, 2020

Awesome

By Vinit D

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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

By Stephen O

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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!!!

By Prashant N

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Oct 8, 2023

,,,,,,

By Harsha V

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Aug 22, 2023

superb

By T S (

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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

By Srinivasan L

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Dec 17, 2017

Great!

By sandeep

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May 29, 2017

Thanks