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

4.6
stars
13,376 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.

PM

Aug 18, 2019

The course was well designed and delivered by all the trainers with the help of case study and great examples.

The forums and discussions were really useful and helpful while doing the assignments.

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876 - 900 of 3,116 Reviews for Machine Learning Foundations: A Case Study Approach

By Rizwan A S

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Aug 8, 2019

Very easy to understand and get familiar with the basic of machine learning through the practical examples.

By Jayaganesh G

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Dec 19, 2017

Learning from real world problem than a toy problem. Very different from others and much practical. Thanks.

By Suresh K

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Aug 12, 2017

Very practical case studies to learn the core concepts of machine learning. Most recommended for beginners.

By Donkena S K G

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Sep 30, 2016

The course is very intuitive and very explanatory. This is very help course to begin with Machine Learning.

By Pavel K

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Aug 5, 2016

A very clear and straightforward course giving a foundation for the following learning of Machine Learning.

By Damian T

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Feb 24, 2016

Great course! It wets your appetite for a more in depth look at the various techniques to machine learning.

By Bhawani S L

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Nov 3, 2015

Very good course to start Machine Learning Basics. Excellent coverage of practical programming assignments.

By Dr. M A H

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Jun 7, 2020

Excellent course materials

Good data collection

Good delivery of lecture notes

Five stars for all hospitality

By Junfeng D

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May 20, 2018

very great course in a case study approach, you will be familiar with all basic algorithms and ML methods.

By 易灿

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Apr 16, 2016

Awesome, very very useful, and intuitive! Hope teachers can introduce some books or papers for us to read.

By De.Sambath M

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Mar 13, 2016

Excellent. Went through the introduction videos and course material. Great one. Thanks for publishing it .

By Hugh A

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May 13, 2022

really good intro to the fundamental principles of Machine Learning ... also ... it really stretched me !

By Muhammad R C S

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Dec 26, 2020

A complete fundamentals of understanding how machine learning works! Valuable to develop my career ahead

By Jason S

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Oct 30, 2019

This was exactly the combination I needed of concept, use case, interpretation, and hands-on application.

By Noam K

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Apr 2, 2019

Nice overview, the case study approach is very useful as well as the actual python notebook assignments.

By Vaibhav G

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Jul 9, 2017

It was very nice. However the iPython assignments became a little redundant and mechanical after a while.

By Bowen C

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Oct 4, 2016

I love this course. I do expect we can learn more about the algorithms though. Overall I love this course

By Md. T H

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Jul 13, 2016

Basically an ML - 101 course. Certainly it is one of the best possible introductory courses on any topic.

By Aku-Jaakko S

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Mar 7, 2016

Hands down, one of the best courses I've ever taken. Exciting, informative and motivating teaching style!

By Neta Z

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Oct 23, 2015

Thank you!

Course instruction was clear and home work was challenging enough to make me have to listen ;-)

By dhatri P

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Apr 10, 2020

The course is very well designed along with python explanation for ML and explanation is very excellent.

By Ritu R

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Oct 5, 2019

Very helpful course, it helps to understand how to use your machine learning concepts in the real world.

By 学洲 刘

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Jan 8, 2018

This is the best course of Machine Learning I have taken part in. Thanks for the teachers and coursera !

By Jorge L

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May 28, 2017

Comprehensive coverage, very well delivered. Entertaining and helpful. Really enjoyed this first course.

By Sameer C

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Jun 25, 2016

A really good course for beginners who want to understand the concepts and not the underlying algorithms