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

12,431 ratings
2,975 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

Aug 18, 2019

The course was well designed and delivered by all the trainers with the help of case study and great examples.\n\nThe forums and discussions were really useful and helpful while doing the assignments.

Dec 19, 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.

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2476 - 2500 of 2,888 Reviews for Machine Learning Foundations: A Case Study Approach

By Sourabh K

Jun 30, 2020

numpy and pandas are more preferable, but the overall experience was good.

By George B

May 17, 2018

Pretty great course. Really enjoyed it and looking forward to new courses

By Jeffrey v S

Oct 31, 2017

Content is good but the delivery is somewhat awkward and chatty at times.

By Brennan W

Feb 4, 2017

Was a good intro to different kinds of ML. Wish we had used SciKit-Learn.

By Nandan S

Mar 15, 2018

very good overall. The last week (Neural networks) is a little too fast.

By Ramesh S

Mar 14, 2018

A good and quick introduction to ML. Like the Case Study based approach.

By Anastasiia

Feb 2, 2018

OK course if you don't have any background knowledge. Graphlab oriented.

By Aaron M

Jul 2, 2017

Seems a bit old but it was a great way to introduce myself to the basics

By Matías G

Oct 7, 2016

Great Course, just felt little weak the last module about deep learning.

By Stuart L

Dec 18, 2015

a good introduction of the topics. I like the ML diagram in each module.

By Lucia d E P

Feb 5, 2018

I enjoyed the course and the fact that it uses Python for the exercises

By Xavier H

Aug 8, 2016

A good introduction tot he tools and possibilities of machine learning.

By Zhe W

Oct 27, 2015

Useful course to get general idea to get onboard with Machine Learning.

By Leon

Oct 1, 2019

Goes through many topics, but not as in depth as one would have liked.

By Jacques J

Sep 8, 2017

Was so good to get some exposure to the different areas of application

By Sandeep K S

Jan 5, 2016

Good course with the overview of different machine learning techniques

By fredfoucart

Dec 10, 2015

A good global introduction and simply explained. With fun as well....

By Ali N

Nov 13, 2015

Really great course content, but the assignments could become better.

By Harshal M

Aug 18, 2017

Great Course!! Helped me learning new things. Great way of teaching.

By federico w

Apr 4, 2016

Great course. Super case driven approach, professors are very clear.

By أحمد ج

Aug 6, 2019

wish to use more common ML libraries, but the content was very good

By Kushvanth R

Jan 21, 2021

All is well, but instructors could have used more common libraries

By Bruno G E

Apr 17, 2016

Just the tip of the iceberg, you'll want to dive in on each topic.

By Tina W

Apr 2, 2019

Good Intro course and familiarize yourself with iPython notebook.

By sami j

Dec 26, 2017

pretty good - wish there was more info on the internals to models