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

4.6
8,944 ratings
2,142 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

BL

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

SZ

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.

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126 - 150 of 2,062 Reviews for Machine Learning Foundations: A Case Study Approach

By Omar A

Oct 09, 2018

Thank you for the amazing course. To be honest this is the first course that I complete on course era. The professors are amazing and the pace of learning is suitable for all levels. I look forward to complete the whole specialization. Keep going :)

By Ganesh P

Oct 15, 2018

Very good f

By Muhammad R

Oct 16, 2018

It nice to learn this course.I want to suggest regarding installation there should guide(Video form) regarding setting up tool for this course.Thank you.

By Ganji R

Oct 20, 2018

Excellent course

By Prashant S

Oct 19, 2018

This is a brilliant stepping stone for Machine Learning world. Basics are being discussed and explained in a very simple manner. thanks to the teachers and Coursera

By Brandon M

Sep 12, 2018

A much better introduction to ML compared to other MOOCs I've taken.

By Giovanni

Sep 14, 2018

This course offers a broad range of examples in ML. Clearly some basic knowledge of linear algebra and other concepts is needed, but I believe it is well structured to help those who're not so strong in math. It really is basic, though, so if you have already some knowledge in ML this will result sometimes a bit slow.

By Shivam G

Sep 14, 2018

Very well designed course.

Emphasizes more on application side and covers primary domains as well.

By Sivakumar R

Sep 18, 2018

Very practical and use case based method allows to understand concepts. Hands on training brings confidence to non-software student like me. Thank you for the valuable course.

By POYIN L

Sep 18, 2018

This course gives a really easy but clear concept for machine learning with examples! I hope I can learn something further with other courses in this specialization.

By Bhisham J M

Sep 22, 2018

I found course content and they way it is designed is perfect for anyone to easily grasp the concepts. I am from non-development background and don't have much grip on python language but it was still smooth and easy for me to progress this course by learning python basics and commands as well which is required for programming assignments. Well done coursera, keep up the good job!

By Nagendra K M R

Sep 22, 2018

Explanations are provided in detail which helps even the beginners to master the Machine Learning. Case studies are very interestinghelpful to master the concepts and gain the confidence.

By Magdi M

Sep 11, 2018

Great case coverage

By Rahul K

Sep 11, 2018

The lecturer's teaching is well organized and presented, which helped me to accept the new knowledge quickly.

By Shreyansh P

Oct 06, 2018

it was very helpful course

By Sathiraju E

Oct 02, 2018

A very well organised course with short videos explaining concepts and also giving a hands-on feel.

Thank you Carlos and Emily. Thank you Coursera.

By Ravindra M

Dec 09, 2015

Case study approach works !

I completed this course and found course materials present intuitive. Following courses go deep in each method.

Thank you Emily and Carlos :-)

A small request to Coursera to provide course completion certificate to free account like Edx.

By Maksim H

Nov 17, 2017

I am really grateful for the effort to put this course together!

By Gwendolyn G

Nov 24, 2015

This is a really good intro course. It's not pitched at a terribly high level of difficult, but it does give you a fair amount of practice. I'm really pleased with it.

By Ram

Jan 23, 2016

Great introduction to Machine Learning with the case study approach. Gives you a quick preview on what Machine Learning entails iwth practica use cases without making you learn a new language and several frameworks before you write your first line of useful code. The course seems to emphasize heavily of the practical uses of machine learning

The instructors have a pretty fun way of interacting with the viewers/students. Instead of reading power point slides. The quality of the content is great, though it can be made a bit more consistent in a few modules. The labs are pretty great and an important part of the course material.

The format of this specialization should serve as a template for future specializations made on Coursera.

By ELINGUI P U

Feb 22, 2016

Very good course if you want to learn machin learning.

By Leandro D

Sep 08, 2017

Excelent approach on the case study, looking forward to the next projects of the specialization

By Yoshifumi S

Jan 23, 2016

Assignments are tough, but so practical !!

By Radomirs C

Nov 26, 2015

Excellent fast paced ML overview with hands-on exercises

By Siddharth S

Aug 16, 2016

Excellent introduction to the promise and applications of Machine Learning.