Chevron Left
Back to Machine Learning Foundations: A Case Study Approach

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

4.6
stars
13,554 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

RM

Feb 3, 2022

I was very disappointed with the exclusion of the final courses and the capstone project. The most interesting part of specialization no longer exists and no plausible justification has been given.

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

Filter by:

2801 - 2825 of 3,163 Reviews for Machine Learning Foundations: A Case Study Approach

By Dominik S

•

Jun 26, 2017

Very nice. I think I learned a lot.

By SUNNY D

•

May 3, 2020

T

h

e

6

t

h

w

e

e

k

a

s

s

i

g

n

m

e

n

t

w

a

s

r

e

a

l

l

y

c

o

o

l

.

By Shishir S

•

May 28, 2017

Good course for the beginners ....

By kulbhushan

•

Oct 27, 2016

Very informative and useful course

By BIAN D

•

Jun 15, 2016

homework could be more complicated

By A d v

•

Jan 9, 2022

i loved it excellent explanation

By Royal P

•

Nov 18, 2020

very knowlegdeful and interesting

By Reginald A L

•

Sep 21, 2020

A good course to learn. Thank You

By Lee

•

Oct 15, 2017

look this approach for beginners!

By Yunqi H

•

Jan 24, 2020

Great intro class but very fun !

By Nitin K

•

May 4, 2017

Pretty good introductory course.

By Arish A

•

Jun 8, 2016

A good introductory level course

By Mario A G J

•

Apr 26, 2016

Good for an introduction class.

By Weiyi W

•

Jun 11, 2018

Quizs are harder than lessons.

By Mehul P

•

Aug 1, 2017

Nicely explain use case of ML.

By Jijo T

•

Oct 7, 2015

I love the hands on exercises.

By Mazen A G

•

Oct 9, 2016

the best introduction for ML.

By Rishabh C

•

Jul 23, 2020

Awesome course to start with

By Rakesh G

•

Apr 15, 2019

A good beginners guide to ML

By RISHAB P H

•

Apr 15, 2020

add more practical's please

By Mahesh B

•

Oct 10, 2019

Good start for ML beginners

By Poornima S

•

Feb 19, 2019

It is designed really good.

By Hyeong R J

•

Feb 3, 2017

Good lecture and practices.

By Marcos

•

Aug 24, 2017

Great introductory course!

By GABRIEL O C D O

•

Apr 16, 2021

The course needs updating