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

4.6
stars
13,493 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

SZ

Dec 20, 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.

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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1101 - 1125 of 3,144 Reviews for Machine Learning Foundations: A Case Study Approach

By Pranjul S

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Jul 4, 2018

A great overview and hands-on machine learning concepts and its applications.

By Abdul B M

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May 6, 2018

Great Course, awsome instructors, really fine course material, Simply Awsome.

By Usha T

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Oct 2, 2017

Very good introductory course to ML. It had just the right amount of details.

By Gene C

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Jul 17, 2017

Great course love the practical introduction to the remaining course modules.

By Shihab H

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Oct 31, 2016

Very easy to follow, well-paced, practical / not just theory, cheesy jokes :)

By Jiansen.Zheng

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Apr 13, 2016

An Awesome course, which is quite suitable for beginners in machine learning.

By Xin J

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Jan 20, 2016

It is a very nice course which is the fundamental course of machine learning!

By Khang V

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Dec 31, 2015

Good course, interesting information and knowledge. I also love the exercises

By Ms. C K C S

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Sep 18, 2020

Excellent course for beginners in Machine Learning. Love to do more courses.

By TANU S A C (

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Jul 30, 2020

I am grateful to join such a awesome training cirtificate by these Intruders

By Kripakaran R

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Nov 10, 2018

Some of the informations are half baked, hope to see them in future classes.

By Yugo G

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May 26, 2017

Excellent course with simple explanation and case study, and easy to follow.

By varanasi k k

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Feb 21, 2017

Best course to learning quickly machine learning and understanding concepts.

By yehongtu

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Sep 16, 2016

This is a very cool course about machine learning. I learned a lot from it.

By Tsung W T

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Feb 28, 2016

Great introduction course that requires few programming and math background.

By purbohadi u

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Dec 4, 2015

I like the way Carlos and Emily explain the course in a simple and easy way.

By Ge Y

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Dec 3, 2015

Good application oriented machine learning course. Thanks for GraphLab team!

By Amol K G

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Aug 23, 2020

Need to upgrade python 3 and updated libraries. Rest of the other all good.

By Erick V

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Mar 2, 2019

Excelente curso, te da una visión general de todo lo que puedes hacer en ML

By Rajeev N

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Apr 30, 2018

Excellent foundation on all aspects, hands on coding exercise is exciting.

By Matthew T

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Dec 30, 2016

Really interesting material thought very enthusiastically. Enjoyed it loads

By Siddharth S

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Aug 16, 2016

Excellent introduction to the promise and applications of Machine Learning.

By Shiva K Y

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Aug 14, 2016

Course is outstanding except it uses a paid library called graphlab create.

By Ranfi J C d A

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Apr 24, 2016

Un curso perfecto para introducirte en el mundo del aprendizaje automático.

By Alexandra P

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Jan 10, 2016

great introduction to machine learning with real world application examples