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

4.6
stars
13,485 ratings

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.

The forums and discussions were really useful and helpful while doing the assignments.

SZ

Dec 19, 2016

Great course!

Emily 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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2576 - 2600 of 3,140 Reviews for Machine Learning Foundations: A Case Study Approach

By Sudeep K

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May 26, 2018

A really nice course for someone who is new to the interesting world of machine learning and all the possible application

By ezz@winning.com

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Nov 13, 2015

Excellent case study approach. Hopefully, other methods-rather than graphlab- will be included as well in future courses.

By faiza S

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Jan 7, 2019

Good as theoretical concepts but labs stick with Graphlab which not commonly used library. But overall good experience.

By Joseph T

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Aug 11, 2016

This course was a good teaser. Everything is very easy and fun. At the same time, you can see how powerful graphlab is.

By Diego F

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Aug 17, 2020

Really good lectures, missed a bit of a complexity and got some problems with the hole turicreate/graphlab transition.

By Sunit K

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May 30, 2020

Very practical course which gives you real world implementations of Machine Learning. Absolutely enjoyed the material!

By Yub B

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Apr 16, 2017

Pretty decent course for beginner to learn machine learning. A case study approach they used is great and interesting.

By CESAR A Q C

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Jul 28, 2021

There are some troubles with the new library but the concepts are clear and the practice was good and entertaining.

By Neel S

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Apr 30, 2020

It's very good and very well understandable course. It cover core concepts of machine learing.

Thank You! Sir and Mam

By Peter W

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Mar 11, 2016

In general a good course, well presented.

4 start only due to some assignment questions not being covered in lectures

By Kevin A

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Jun 29, 2017

I haven't yet finish this course but is a excellent introduction for begin to study in this computer science field

By ANKIT S

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Jul 5, 2020

i would rather give 5 but as i wasted lot of time due to graphlab so i have take one star for that my satisfaction

By Sarra Z

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Jan 22, 2020

I liked this course, it is really based on study cases approaches and covers many problematics in machine learning

By Ankit T

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Aug 29, 2019

The course provided by Course era was really very good. I want to thank to Course era to give me this opportunity.

By Chris

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Jun 28, 2021

Very nice teachers and good overall knowledge. However the discusion forum is dead and learning materials are old

By Bhaumik C

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Jul 17, 2020

Faculties were too good and explained very nicely. And I would recommend others this course for machine learning.

By golap h

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Jul 2, 2020

This machine learning course is really effective for beginners.I have learned many basic topics from this course.

By weiyuan x

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Apr 12, 2017

Good start course. It seems some information not covered so sometimes it is difficult to understand the content.

By Christophe M

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Nov 8, 2015

Very didatic approach to machine learning. Easy access and still powerful technique to understand how it works.

By Bhaargavi A

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May 8, 2018

Good Course. Teachers have taught it well and the jupyter notebooks are good and give a good deal of practise.

By Soham K

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May 28, 2020

Overall it has been a great experience. But in my opinion, the course videos should be updated to TuriCreate.

By Kuldeep K

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May 11, 2020

Kindly change the GraphLab package system, the majority of the compiler doesn't support this.

Else it was good

By Azhar B T

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Sep 16, 2019

the course is good but rely on graphlab and lack of hands on with python is the reason i cannot give 5 stars.

By Philip L

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Nov 12, 2016

Some quiz questions' answers are incorrect and instructors need to update the quit to reflect correct answers

By Islam M

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Apr 19, 2016

-great introduction .

-go through a lot of exciting topics.

-but the implementation part is boring something.