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

4.6
stars
13,492 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

SZ

Dec 19, 2016

Great course!

Emily and Carlos teach this class in a very interest way. They try to let student understand machine learning by some case study. That worked well on me. I like this course very much.

BL

Oct 16, 2016

Very good overview of ML. The GraphLab api wasn't that bad, and also it was very wise of the instructors to allow the use of other ML packages. Overall i enjoyed it very much and also leaned very much

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1601 - 1625 of 3,143 Reviews for Machine Learning Foundations: A Case Study Approach

By Kyrylo S

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Dec 28, 2015

Excellent presentation of material

By Kiên T

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Mar 11, 2024

The useful overview for the start

By Joseph S

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Jun 30, 2021

The most satisfying course so far

By Keyur M

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Jun 2, 2020

A very good course to starting ML

By Rohit A

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Jun 1, 2020

this is very use full for learing

By Koutaiba O A

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May 21, 2020

I liked the content of the course

By NAGARJUNA T

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Apr 28, 2020

Am so Happy to learnt this course

By Smrithi P P

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Apr 18, 2020

This course helped me lot. Worthy

By Jithesh R

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Nov 30, 2018

Great Experience...! Loved it...!

By Pritesh G

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Jul 20, 2018

Good material. Enjoy the Course.

By Rishab R

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Apr 21, 2018

Very well presented and organised

By George P

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Jul 20, 2017

Very good and smooth introduction

By Mai T

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May 17, 2016

Very easy to follow and enjoyable

By César A P M

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Mar 7, 2016

It is very understandable course.

By songwei

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Jan 12, 2016

cool class about machine learning

By Alfonso d F

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Nov 30, 2015

Great introduction to ML concepts

By Rubens P

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Oct 20, 2015

Good examples and very practical!

By Thejaa V r

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Nov 10, 2021

useful for my career development

By fernandes m

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Aug 28, 2020

Very good, best that I specteted

By Chiranji L C

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Mar 27, 2019

practical exposure is excellent!

By Ankita M

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Nov 20, 2018

great content and good exercises

By esther@lumastech.com

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Jul 17, 2017

very crisp and clear explanation

By Fernando B

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Feb 21, 2017

Best Course on ML yet on the Web

By Laura G

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Feb 20, 2017

Great start to Machine Learning.

By Dmytro K

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Jan 22, 2017

Great intro to Machine Learning!