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

4.6
stars
13,547 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

DS

Sep 27, 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!

SS

May 18, 2020

The course was very informative but I face a lot of problems in installing Graphlab and Turicreate. I request the Mentors please use the Pandas data frame in place of SFrame. The mentors are cool.

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1826 - 1850 of 3,161 Reviews for Machine Learning Foundations: A Case Study Approach

By Shuchih N

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Nov 4, 2020

QUITE good

😊😊😊😊

By rs

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Oct 22, 2020

Usefull to learing

By JAKKA S P S

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Oct 5, 2020

Its perfect course

By Sarthak S

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Aug 23, 2020

very nice and easy

By Diego L

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Aug 5, 2020

Excelente Curso!!!

By Harshita K

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Jul 14, 2020

Good for beginners

By Moe K O

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Jun 28, 2020

I love this course

By Nagarajapandian

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Jun 16, 2020

Very useful course

By IDOWU H A

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May 20, 2018

These Traininers a

By Jing

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Aug 14, 2017

Good for beginners

By Muhammad U

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Aug 11, 2017

Excellent Teaching

By Nancy Q

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Feb 13, 2017

highly recommended

By Adrian B

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Sep 14, 2016

Very recommendable

By Chen Y

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Feb 18, 2016

It's a neat course

By Vlad G

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Jan 29, 2016

amazing experience

By DEVINENI T

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Oct 7, 2022

its very helpful

By Fevzi E K

•

Oct 11, 2020

gerçekten çok iyi

By SHARUKH A

•

Jul 18, 2020

great course.....

By Bhavya D J

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Jun 15, 2020

amazing course...

By Abhay S

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Jun 14, 2020

i love course era

By Ridwanul H T

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Apr 11, 2020

Excellent course.

By Shiwanshu K

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May 19, 2019

Beautiful course!

By Yaakov M

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Jun 16, 2017

Nice introduction

By Bum-Joo C

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Jun 2, 2017

Good! and Useful!