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

4.6
stars
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

SS

May 19, 2020

The course was very informative but I face a lot of problems in installing Graphlab and Turicreate. I request the Mentors please use the Pandas data frame in place of SFrame. The mentors are cool.

AH

Mar 28, 2022

very nice course.If you have basic knowledge of python datastructure then this course is best to start data science.All contents are beginner friendly which makes this course easily understandable.

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2776 - 2800 of 3,159 Reviews for Machine Learning Foundations: A Case Study Approach

By Harsh R

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May 19, 2020

The course is little bit outdated.

please update

By shadab h

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Nov 18, 2018

A must do course to start with Machine Learning

By Deleted A

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Jan 21, 2019

great class to learn machine learning hands on

By Spike Y

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Nov 30, 2017

I like the explaining about ipython notebook !

By Abid A S

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Aug 3, 2017

Good one to start learning some basic concepts

By Amilkar H

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May 11, 2019

It's a very good introduction to the subject.

By Roberto E

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Nov 29, 2016

Interesting but a bit weak for my purposes...

By Matic D B

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Feb 9, 2016

Great course. Maybe a little bit too basic.

By Jayant S

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Oct 23, 2019

Explanations must be more comprehensible.

By Flavio B

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Feb 10, 2016

Most of it I already knew, but was nice.

By GOLLAPUDI R C

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Nov 24, 2015

A good introduction to machine learning

By Charupriya S

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Jul 21, 2020

It's really nice course for beginners.

By Sankara S K

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Sep 23, 2018

This is a good 101 course to start ML.

By Nilkumar P

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Jun 10, 2020

So far Best Course on Machine learnig

By Jakkamsetti S D

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Apr 27, 2020

It's really good studying in Coursera

By Om D

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Dec 4, 2019

Nice Course with Detailed explanation

By Oleg S

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Jul 21, 2017

very difficult...a real challenge....

By JUTUR S V

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Jun 24, 2020

Easy Understanding and good teaching

By Alberto M

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Sep 22, 2018

Good overview but basic information.

By Neilmani S

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Feb 14, 2018

It was one of the amazing Course !!!

By Yang W

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Mar 10, 2016

A very practical course. Like Emily.

By Priyanka J

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Jun 18, 2020

Good work but need more explanation

By Abhinav M

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Apr 1, 2018

Great material to try out ourselves

By Dominik S

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Jun 27, 2017

Very nice. I think I learned a lot.

By SUNNY D

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May 3, 2020

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