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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

DP

Feb 14, 2016

With a funny and welcoming look and feel, this course introduces machine learning through a hands-on approach, that enables the student to properly understand what ML is all about. Very nicely done!

AH

Mar 27, 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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1701 - 1725 of 3,157 Reviews for Machine Learning Foundations: A Case Study Approach

By Anji B P

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Jun 6, 2019

Good Course with case study

By Chen G

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Feb 27, 2017

A great introductory to ML.

By Awantik D

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Feb 10, 2017

Perfect for getting started

By Sam C

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Oct 23, 2016

interesting to follow alone

By Oleksii R

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Jun 4, 2016

Great course. Thanks a lot.

By Vijai K S

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Dec 5, 2015

So far it has been awesome.

By Mustapha B

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Jul 19, 2022

Excellent !! thank you !!

By Merve E U

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Dec 13, 2020

Thank you for your support

By Ben R

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Oct 17, 2020

great course very useful!!

By T P R

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Aug 14, 2020

its best to learn this way

By Tianshu W

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Jul 28, 2020

Loved it! I learned a lot!

By Sinmileoluwa T

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Jun 23, 2020

This course was excellent!

By Christy C R

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Jun 5, 2020

Great course for beginners

By Shreyansh P

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Oct 6, 2018

it was very helpful course

By Roxana N V

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Mar 26, 2017

Great introductory Course.

By Ahtasham H

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Feb 5, 2017

Amazing Learning approach.

By Socrates M

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Nov 20, 2016

It is really cool course .

By Rabish K

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Oct 21, 2016

Excellent. Very Intuitive.

By Danish R

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Oct 14, 2016

A good introductory course

By Ehsan T

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Oct 11, 2016

the best Course i ever see

By Vikash M

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Sep 13, 2016

Great course for starters!

By felix a f a

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Feb 21, 2016

Really Good Introduction!!

By Soumya R

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Feb 4, 2016

Great for beginners in ML!

By Deleted A

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Jan 6, 2016

Great intro to the ML area

By Fangyi Z

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Nov 19, 2015

This course is good for me