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

4.6
stars
12,448 ratings
2,977 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

PM
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.

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

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2351 - 2375 of 2,891 Reviews for Machine Learning Foundations: A Case Study Approach

By Anshul T

Dec 26, 2015

A good course to show the extent of what is coming up in the specialization, a quick and dirty hands-on approach and pleasant course tutors.

By Kunnathupeedika M B

Sep 8, 2020

The course is well structured with a mix of theory and python hands -on. Outdated python packages are used though in the hands-on section.

By Jiancheng

Dec 6, 2015

Great course design and case study! More detail about algorithm will be better, but maybe you can find them more in the following courses.

By TE Z

Dec 21, 2018

A good way to get familiar with the machine learning things. it provides the very basic concepts and way of thinking from ML perspective.

By Dina T S

Feb 10, 2016

The overall course was very useful.

However some topics I found difficulty to understand the idea even after repeating the video 3 times.

By Lucas M

Nov 10, 2018

I couldn't install Graphlab create on my own environment, so I had to translate almost everything to Pandas/SKLearn.

Great content, still

By Yogesh D

Apr 14, 2016

its a good course to get hands on development with machine learning algorithms. but one disadvantage being its using preparatory library

By ZHENG W

Sep 17, 2017

Great intro course to machines learning. For those who perhaps learnt back in university, it can also serve as a great revision course.

By Maen A

Jul 18, 2019

The course content is great, it would be even better if the assignment were a bit more challenging rather than following instructions.

By Marcello G

Dec 1, 2015

It'd be 5/5 if it used scikit-learn, instead of proprietary software (albeit with 1yr free to use license for non-commercial purposes)

By Oliver K

Jun 3, 2018

this is a good first introductory course on various machine learning algorithms. Helped me a lot to understand the basic principles.

By William P

Apr 22, 2016

Installation of the recommended toolkit is tricky and very expensive if perused non-academically.

Content is clear and well presented.

By James C

Jun 29, 2016

Good primer to Machine Learning - uses real world examples to introduce different machine learning concepts in an interesting way.

By Gello M V

Jan 3, 2016

Interesting! The lecturers were good. Though sometimes, things get boring. But overall, the subject and the quizzes were exciting!

By fetty f

Feb 19, 2016

This course is very fun especially the lecturers. Beside that, all the topics have contextual sample that very easy to understand

By Balasubramanya S

Aug 25, 2018

Good course for understanding basics about ML, it will be good for professionals to start same course with Open source libraries

By Ching C H J

May 20, 2018

Lots of problem with graphlab installation.... and turicreate is not supporting all the functions the same way as graphlab does.

By Ahmed N

Feb 24, 2017

This course is very important for me and i really learned many things of machine learning concepts and its important study case.

By Sylvia L

Apr 10, 2016

Very practical and the contents are good. But the quizzes are just too simple and the analysis on the cases are not deep enough.

By yehoshua c

Jan 6, 2016

I really liked the enthusiastic lecturers and the "easy" to learn approach. with that the exercises were easy and meaningful :)

By Sheng-Qi S

Oct 30, 2016

课程不是很难,没有怎么涉及详细算法的实现,我是学完Stanford的ML过来的,所以感觉UW的有点像开胃菜,不过这门课介绍了ML的一些概念,并且介绍了Jupyter Notebook这个强大的工具。总之,不虚此行,感谢UW!Thank you UW !

By Vaidas A

Sep 14, 2016

Very basic overview using GraphLab Create to emphasize intuition - if you are familiar with ML concepts might be a bit boring.

By Ben K

Feb 22, 2016

A good course, but I found the programming exercises fairly underwhelming. It is just an overview course, so it is what it is.

By Fabio V

Feb 6, 2016

Real life applications....thrust them till the end (even if I'm not comfortable learning from such good but branded teachers)

By NIKHIL M

Aug 16, 2020

Very interesting Course , I have learned much more about machine learning.

Thank you coursera for this informative knowledge.