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

4.6
stars
12,445 ratings
2,976 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

SZ
Dec 19, 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.

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

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2776 - 2800 of 2,889 Reviews for Machine Learning Foundations: A Case Study Approach

By Marco M

Dec 4, 2015

Too much synthetic on very important parts, too much focused on graphlab

By Alejandro V

Nov 13, 2020

TuriCreate is not the apropriate tool for practical Machine Learning

By Pawan K S

May 15, 2016

Nice introductory course but too much dependence on graphLab create

By Jesse W

Dec 24, 2016

It is better if allow me upgrade only when I finished this course.

By Tushar k

Nov 30, 2015

Good course to begin machine learning with but it's too easy !!

By Konstantinos L

Jan 8, 2018

Nice course but too easy. Assignments should be more difficult

By Felipe A S S

Jan 23, 2021

The libraries used on the course are a little bit unsopported

By Atharv J

Sep 14, 2020

The course should be taught in pandas rather than graphlab.

By Max F

Jan 10, 2016

Not a bad course, but extremely basic. Was expecting more.

By Adrien L

Feb 2, 2017

No good without the missing course and capstone projects

By Himanshu R

Apr 16, 2020

It uses turicreate which is not available for windows .

By Aleksey C

Dec 11, 2016

....mmm fsdfg gsgsd sgsdgsdg sdsdgsdg ggsgsd sgdsdgsg

By HITESH D

Jun 15, 2020

Installing software parts gave me a very hard time.

By Bastian M P

Jun 1, 2016

Could go a little more in detail on the algorithms.

By Jaime O

Jan 31, 2017

The Deep Learning part needs to be improved

By Chen S

Oct 26, 2015

Very basic, the quizzes aren't clear enough

By Li-Pu C

Oct 29, 2020

A little bit too easy, but good for rookie

By Harsh V K

May 8, 2019

Should use Python 3 instead of Python 2

By Phú L L H

Apr 3, 2021

sofware guideline is quiet useless

By Yu G

Feb 7, 2021

No idea what to write here...

By Jorge A C C

May 29, 2016

It is a very simple course.

By RAGHUPATHI R R

Jun 25, 2020

Good for knowledge

By Fredick A S

Apr 6, 2018

No python..

By Nasimul J F

Aug 16, 2020

THANK YOU.

By Kai C

Nov 24, 2015

Too easy