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

4.6
stars
13,532 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

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.

MK

Jul 20, 2019

A great course, really designed to understand the underlying core concepts of machine learning using real-life examples which takes you through all that with little to no programming skills required!

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1676 - 1700 of 3,157 Reviews for Machine Learning Foundations: A Case Study Approach

By QIANGQIANG G

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May 7, 2020

well-organized course, thanks

By Santosh K D

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Jun 4, 2019

Best course for introduction.

By abbas s

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Mar 1, 2019

wonderful learning experience

By 陈兵

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Mar 14, 2018

very good material, good work

By Monisha M

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Jun 22, 2017

A great course for beginners!

By Raymond Z

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Aug 10, 2016

very cool practical approach!

By Raghad A

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Feb 10, 2016

Very well constructed course.

By Xi X

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Sep 21, 2022

great learning experience!!

By Kode K V

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Nov 28, 2021

They teach very beautifully

By Vinh N X

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Oct 8, 2021

i feel the course is so good

By ADARSH K D I S

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Jan 4, 2021

too much helpfull ..thanks:)

By PAVITHRA B

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Sep 29, 2020

Excellent Fundamental course

By Kranthi K G

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Sep 15, 2020

Perfect course for beginners

By Hemanth

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Jul 8, 2020

very helpful and informative

By Soumya M

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Jun 28, 2020

Really helpful for my career

By Rajyavardhan S R

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Jun 29, 2019

Amazing Course, learnt a lot

By Aakash D S

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May 13, 2019

Simply Awesome, Thanks a Lot

By Ian M C

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Nov 26, 2018

It was a great introduction!

By Charlie C H

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Jun 10, 2018

Very useful and clear lesson

By Giuseppe S

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Jan 26, 2018

Nice course ! I enjoyed it !

By Liekens W

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Dec 16, 2016

Great course for starting ML

By Prashanth P P

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Nov 25, 2016

Loved it. Simple and crisp !

By 尧浩华

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Sep 30, 2015

It is very helpful my study!

By Yash S

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Apr 6, 2021

awsome course for beginners

By Andres F R V

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Nov 17, 2020

very good,,,, i am happy. i