Chevron Left
Back to Machine Learning Foundations: A Case Study Approach

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

9,110 ratings
2,174 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


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


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.

Filter by:

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

By Luis D

Jun 04, 2016

Great Course

By Thales P d P

Jan 15, 2016

Excellent material to introduce such a broad topic as Machine Learning. The highlight is definitely the video lectures with Carlos and Emily whom never lose sight of the didacticpurpose and target audience for the course!

By Lion F P d S

Dec 16, 2015

Very Good Course. Dato features are fantastic

By chen y

Nov 20, 2015

very interesting course for introducing machine learning

By 藍元宗 ( L

Oct 17, 2015

Very interesting and informative course. Thanks, teachers.

By Brian B

Dec 04, 2015

Great, and very easy to learn the foundations of ML!

Case-based study is a great way to teach this kind of material for beginning ML students!

By James Z

Feb 29, 2016

A great lesson to learn about machine learning. Two teachers are very funny and the quizzes are not very hard.

By Nitin S

Feb 07, 2016

Awesome course!

By Rebekah H

Jun 09, 2017

I felt this course did a good job introducing the student to Machine Learning. The examples and hands on assignments brought the concepts home. I was able to use the knowledge immediately at work.

By Siddharth

Jul 29, 2016

Excellent course with great instructors and course content.

By Dennis S

Apr 28, 2017

Great presentation of the topic and fitting complexity / depth for an introduction.

Way better then all the other courses i tried before. Great instructors and concept!

By Blaine T

Jul 30, 2017

Very good lectures, good pace, engaging lecturers

By 杨铭宇

Jul 01, 2017

A so good course with so lovely teathers.

By Carlos A M T

Jul 30, 2017

Very practical approach to use in real business applications

By Amit K

Aug 16, 2016

Sets a good foundation for getting started with Machine Learning.

By Sarn

Dec 05, 2015

Excellent intro to Machine Learning.


Feb 11, 2016

Excellent Course .

By Richard G

Jun 06, 2018

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

By Pablo A

Jan 17, 2016

I enjoyed the course very much!! I think the instructors are great and the method used for teaching is engaging and challenging. Congrats.

By Raymond

Dec 19, 2016

This Course really helped me to understand the basic concepts in Machine Learning.

By ilyas c

May 30, 2017

Clear and easy to follow

By Deividas K

Jan 08, 2017

Great introduction to machine learning and its various concepts.

By K.A R B

Dec 12, 2015

Good course. In-depth information about machine learning

By 郑蔡云

Nov 29, 2017

many tools and practical methods are introduced. It would undoubtedly be a pleasant experience to take this course.

By Dawei L

Dec 26, 2016

This course is quite advanced. You should do this after you have finished the one from Stanford U.