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

4.6
9,049 ratings
2,162 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 19, 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 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 2,081 Reviews for Machine Learning Foundations: A Case Study Approach

By AP

Mar 20, 2016

Easy introduction aimed at beginners, with good content and practice

By Niraj U

Nov 03, 2016

It is a solid foundation to Machine learning.

By mohammed e e

Feb 09, 2016

it's the best course of machine learning i'have token in my life,the method of teaching is great, the content is really fantastic, the instructors teaching skill is excellent and it cover lots of real world artificial applications so it's very amazing

By RAMESH K M

Feb 08, 2016

Course is really taking a practical approach towards machine learning, with theory and practical classes side by side. Thanks to Course era and University of Washington for providing a wonderful opportunity.

By sharod r c

Mar 19, 2016

A really awesome course taught in a new and scientific way !!

By Santosh G

Jun 10, 2016

The course is Awesome. I really liked the case study approach and the instructors are cool.

By Ganesan P

Jun 05, 2016

it was a good introduction to concepts. would recommend the course to beginners in ML

By Adrian B

Sep 14, 2016

Very recommendable

By NAMAN J

Apr 20, 2016

Good Content!

By Willem v G

Mar 20, 2018

Both instructors are very good at explaining the concepts of ML. Also the practical part of the course working with Python and Jupyter notebooks definitely helps in understanding the concepts and apply them right away.

By Alex B

Jan 03, 2017

Great mixture of theory and practice. Really enjoyed working through the IPython notebooks!

By rohit s

Feb 10, 2016

Fresh approach towards ML. Grpahlab makes coding very easy. Deep learning explained in a very easy way to understand. Waiting for other sessions to start.

By Dipanjan S

Sep 28, 2015

Excellent course, with really good lectures, material and assignment. Plus the professors are really amazing and their enthusiasm is really refreshing and makes the class more interesting. Loved it!

By Alexander A S G

Dec 26, 2015

ok

By David L

Sep 23, 2016

Very up to date and practical.

By Siddharth M

Dec 18, 2015

An excellent introduction to different machine learning algorithms. As expected from an introductory course, this deals with only a top level overview of the tools, without getting bogged down with the details and mathematics of the underlying algorithms. I would recommend this course for those who want to familiarise themselves with using out of the box algorithms provided by different software packages.

By Kerry J

Aug 25, 2016

Great introduction to machine learning.

By Adam J R

Nov 21, 2016

Excellent instructors made the course very worthwhile.

By Ashley A

Nov 14, 2016

Really liked the course and the teachers. Would have preferred more detail on the quizzes so I didn't feel as lost as I did some of the times while trying to piece together what a question meant.

By Cheng C

Jan 24, 2016

Amazing introduction course for Machine Learning beginner!

By Aurelije Z

Mar 06, 2016

great course - i really like it.

Aurelije

By Zhao Y

Feb 18, 2016

Interesting approach, clear and organized structure, well prepared contents and up-to-date implementation techniques

By Robert G

Oct 29, 2015

These instructors are among the very best I have encountered as a veteran of dozens of MOOCs. Their expertise in the subject matter, presentation and pleasant manner made this a highly pleasurable learning experience.

By Abhijit c

Jan 15, 2018

This really helped me understand basics about Machine learning concepts. programming exercise were very relevant . thanks

By Satrajit P

Mar 25, 2017

Excellent coverage of the underlying concepts.