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

4.6
stars
13,527 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

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

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.

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1076 - 1100 of 3,156 Reviews for Machine Learning Foundations: A Case Study Approach

By Ashish S

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Apr 23, 2017

A very good and user friendly course . The practical examples are of great help.

By Sameer M

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Feb 8, 2017

Excellent Course! Must do for everyone who wants to start with machine learning.

By Ecaterina M

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Oct 28, 2016

Incredibly helpful for somebody with no previous experience in machine learning.

By James W

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Apr 29, 2016

excellent material for getting a feel of different machine learning applications

By Daniel M

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Dec 23, 2015

I love this course. I found it informative and the materials easy to understand.

By Faith S C

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Sep 20, 2021

I love the manner in which the concepts were explained. Beautiful slides too!!

By Masrur A P

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Jul 23, 2021

Such a really nice course to learn. From here I learned many important things.

By Pablo V

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Nov 23, 2020

It was beyond my expectations. I'm already looking forward to the next courses.

By Hadeer T

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Aug 1, 2020

it was very useful to me to join this course really thank you for your efforts.

By Kishore S

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Dec 22, 2019

Lecturer explained the course very clearly and course designed really excellent

By George

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Dec 12, 2019

the course has been very helpful in my development in the field of data science

By PUYANG H

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Jun 16, 2019

Overall the good start for a beginner, but seldom about the theoretical things.

By Hitesh H

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Jun 2, 2018

A very pragmatic approach. Complex concept were made simple to grasp and apply.

By Khalil A D

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Jun 25, 2017

well presented. clear. does not shy from details without being heavy. good job.

By Javier F

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Mar 20, 2017

simple, self explanatory and self enought to start playin with machine learning

By Manikandan R

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Feb 27, 2016

Awesome course

one will learn tech as well as bit of theory.

Will help devs a lot

By Claudio S

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Feb 27, 2016

Very interesting and fun overview of the different machine learning techniques.

By Girisankar S

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Oct 22, 2021

HAPPY TO LEARN MORE ABOUT MACHINE LEARNING .ABLE GATHER THE INFORMATION EASILY

By serdar b

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Oct 27, 2020

I really like the style they teach and super useful to understand the concept.

By wiwi

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Sep 10, 2020

Excellent as an introduction course. Attract the interest in machine learning.

By Sonal M

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Jul 7, 2020

This course is actually very good and lost of things I learnt from this thanks

By Ishan B H

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Apr 29, 2020

Nice course. Its it nice to have if you use sci kit or other libraries. 5stars

By Parab N S

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Oct 12, 2019

Excellent course on the basics of Machine Learning by University of Washington

By John R

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Jun 6, 2019

Energy of teachers and quality of content made this super fun and informative.

By Richard G

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Jun 6, 2018

Good introduction for people looking more for hands on than academical theory.