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
13,531 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 2, 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.

RH

Jun 8, 2017

I felt this course did a good job introducing the student to Machine Learning. The examples and hands on assignments brought the concepts home. I was able to use the knowledge immediately at work.

Filter by:

2076 - 2100 of 3,157 Reviews for Machine Learning Foundations: A Case Study Approach

By Lumbha r

•

Jul 4, 2020

excellent

By chandana m

•

Jun 26, 2020

excellent

By Cristin R

•

May 7, 2020

Excellent

By Dani D

•

May 6, 2020

EXCELLENT

By Srikanth G

•

Apr 28, 2020

Excellent

By bardock s

•

Apr 28, 2020

very good

By KORGAONKAR S S

•

Apr 13, 2020

Loved it.

By eric g

•

Mar 6, 2020

best ever

By Mopuru V R

•

Jan 12, 2020

Thank you

By Nathan W

•

May 15, 2019

Completed

By Hasan H J

•

Apr 2, 2019

excellent

By DIVYANSH S

•

Feb 3, 2019

EXCELLENT

By Muhammad A N

•

Dec 6, 2018

Excellent

By jorge j l c

•

Sep 5, 2018

Excelente

By blues星星

•

Aug 17, 2018

m满分，讲的很不错

By 肖攀

•

Dec 18, 2017

很满意，因为有中文

By Sérgio E L

•

Oct 30, 2017

Excellent

By Deleted A

•

Sep 10, 2017

very good

By divas v

•

May 2, 2017

Excellent

By fan c

•

Mar 20, 2017

深入浅出，通俗易懂

By Jake G

•

Dec 6, 2016

Loved it!

By threefish

•

Aug 30, 2016

very good

By Rajiv B

•

Aug 21, 2016

Loved it.

By 于飞飞

•

May 14, 2016

very good

By Xinwei L

•

May 2, 2016

very cool