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

4.6
stars
13,379 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

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

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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1026 - 1050 of 3,117 Reviews for Machine Learning Foundations: A Case Study Approach

By 何益帆

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Feb 26, 2018

It is a perfect course about ML,especially for the students without much backgrounds.

By Paul M

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Feb 4, 2018

I like the case study approach. Much easier and more relevant way to learn the topic.

By Arthur Z

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Feb 24, 2017

A really nice appetizer to begin this specialization. The professors are excellent.

By Jifu Z

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Jul 22, 2016

Good class, But it would be much better if the quiz is open to those who doesn't pay.

By Deepak G

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Jun 24, 2016

I have tried several introductory Machine Learning Courses. This is the best of them.

By Ganesan P

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Jun 5, 2016

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

By abhijit s

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Feb 8, 2016

This course is one of the best MOOC i have attended, best approach and nice hands on.

By Robert R

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Jan 5, 2016

Great way to provide a conceptual overview before getting bogged down in the details!

By Yifei L

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Dec 3, 2015

Very clear and detailed introduction with practice!

Looking forward to coming courses!

By Prachuriya M

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Nov 18, 2020

Very nice Course for beginners to get started, loved all examples and learned a lot.

By Ribhu G

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May 23, 2020

Very wonderfully taught and it was so lucid to learn from Carlos and Emily. Thanks!!

By Yanyan J

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Jun 20, 2018

Good overview, well structured, covers good breadth of topics in product management.

By Zakarie H

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Jul 8, 2017

I do really enjoyed it, the instructor knows the material and makes it fun to follow

By Deleted A

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Nov 25, 2016

Excellent Course for those who want their fundamentals to be very clear and precise!

By Dhruv T

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Jan 18, 2016

The teachers are very good. Makes the rest of the specialization even more exciting.

By Zhihong C

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Oct 13, 2015

A very nice and effective approach. It makes the complicated problem easier to take!

By Santhosh K J

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Jul 17, 2020

It was actually a good experience learning machine learning in this problematic way

By Manali T

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May 27, 2020

Happy and satisfied with whatever I have learned and gain Knowledge in this course.

By Ben D

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Oct 25, 2016

Very good overview of the type of thinking required to do Machine Learning on data.

By Pujin W

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Oct 4, 2016

This course is fundamental to machine learning and helps me to grasp the idea of it

By Yihong C

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Mar 27, 2016

a really interesting and efficient way to help students understand machine learning

By Deleted A

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Dec 4, 2015

Excellent introdutory course. The only downside is the use of proprietary software.

By Favian D

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May 28, 2020

This is the best online course I attended so far. It is easy to understand and fun

By Amoghavarsha B

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Oct 28, 2019

Good course for ML beginners! Introduces us to the world of possibilities with ML.

By Kaybee K

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Jan 25, 2017

As a totally new Jupytor learner, I've enjoyed this appetizer course fully enough.