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

9,104 ratings
2,172 reviews

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


Dec 20, 2016

Great course!\n\nEmily 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.


Oct 17, 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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226 - 250 of 2,093 Reviews for Machine Learning Foundations: A Case Study Approach

By David E

Mar 04, 2016

A remarkable introduction to key approaches to Machine Learning. I'm excited for the coming courses!

By Jignesh K

Aug 29, 2016

This is a great introductory course on Machine Learning.

By Nelson P

Oct 30, 2017

Great introductory course to ML! I learned some valuable insights by building actual models using GraphLab. After taking this course, you'll have the foundations and overview of machine learning to take the follow up courses in the ML certification by same instructors or take any other ML course available out there. Highly recommended.

By Daniel T

Oct 09, 2016

A fantastic course! The case study approach really makes a difference. I can't stand purely theoretical courses so this one really stands out. Best ML course online hands down.

By Nitin K

Aug 30, 2016

A very exciting introduction to Machine Learning

By Marcus C

Feb 08, 2016

great course. This covers all types of machine learning techniques deep enough to get a basic idea how things work. Enjoyed a lot. Instructors are really fun to learn from.

By Perumal R S

Jan 29, 2017

great introduction to basics of machine learning concepts with hands on programs.Loved it.

By Sruti R

Feb 22, 2018

If you are looking for a course to find out what machine learning is. This is a great course. I only completed the first course so far and It has given me a basic understanding of what machine learning is about, the basic techniques, introduction to software used for machine learning and a look at what's ahead to deepen the learning if I choose to pursue this line.

By Neta Z

Oct 23, 2015

Thank you!

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

By Shyamgopal K

Apr 21, 2016

Outstanding course. Case Study model is awesome

By Ross H

Mar 06, 2017

Well structured and engaging.

Quality videos, good pacing. Tools were interesting to work with

By Pankaj K

Sep 25, 2017

Nice overview to ease into all the content!, Only bad this is they use sframe :( either make it opensource and in the mainstream use or provide the assignments in sklearn!

By Lesly A F

Jan 15, 2016

Superb course - Anyone can easily learn. Case study approach is the right way to learn ML

By Mark T

Jan 01, 2016

Awesome material and organization. Also, real fun chemistry between the two instructors (they MUST be married or something!)

By Rick P

Aug 14, 2016

Emily and Carlos provide a very fun and informative introduction to ML! I really appreciated getting a "blackbox" overview of the various ML methods before doing a deep dive into the algorithms. GraphLab and the interactive iPython sessions are great!

By Omar S

Aug 22, 2016

A Brilliant introduction to Machine Learning, I've tried several courses before but none of them got me engaged like this one. The instructors have a lot of knowledge and present the material in a very easy to understand way. Also the assignments and technical work is really engaging and challenges you to really learn the language and the concepts.

By Tianyu Z

Jun 14, 2016

awesome course, a really good course to start your data science class. the software is a little uncommon tho.

By Anjali C

Nov 20, 2015

Learned a lot !!

Looking forward to other courses in specialization :)

Appreciate the enthusiasm of both professors.

By s.g.sridhar

Nov 28, 2015

I am in my third week.Its really amazing as I progress in the course.

By Benjamin V

Aug 01, 2016

Emily and Carlos are great teachers and a lot of fun. It's a hands-on review of several methods without going too much into detail.

By Christine S

Nov 09, 2015

Course is well organized, lectures explain learning concepts very well. And using python notebook examples to show machine learning uses are very unique and quite easy to follow. The assignments may not have been as challenging as some other school's courses, but overall, this is a great course for those who would like to have a practical approach to apply machine learning to solve data problems.

By Ted T

May 05, 2017

I love practical case study approach!!! Great!

By Bharat R

Jul 30, 2017

This course is a great way to get adequately detailed knowledge of Machine Learning Algorithms. The approach to it (case study based) makes it so much more fun and enjoyable that you can really apply yourself to it. The professors have simplified the most complex topics and explained it amazingly well. Happy to have taken this course.

By Sivashankar G

Jul 17, 2016

This course is the right choice for someone who wants to get a high-level overview of the various fundamental concepts in machine learning and provides the zeal to pursue further. Concepts have been explained by the lecturers really well and quizzes and assignments help us to validate our knowledge of the concepts in a seamless manner.

By Caio V

May 10, 2018

Proud of seeing a Brazilian at this level!! And really excited to the coming lessons! Thanks all