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
13,544 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

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.

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.

Filter by:

2026 - 2050 of 3,159 Reviews for Machine Learning Foundations: A Case Study Approach

By Rogerio B

•

May 14, 2016

Excellent!

By Andrey B

•

Apr 9, 2016

Thank you!

By Pedro V H S

•

Mar 5, 2016

I loved it

By Veceslav K

•

Dec 29, 2015

Super fun!

By Andres F Z M

•

Sep 26, 2024

Very good

By Jorge L U V

•

Oct 3, 2023

Excelente

By Ritam G

•

Apr 12, 2023

very good

By Muhamad H

•

Dec 30, 2022

very well

By Christian J S

•

Jul 22, 2022

excellent

By Chaima E O

•

Apr 12, 2022

excellent

By Varuni N R

•

Mar 23, 2022

Excellent

By Charanya r Y

•

Jan 30, 2022

excellent

By ARBAZ A

•

Jan 23, 2022

excellent

By Vyshnavi G

•

Jan 22, 2022

excellent

By rasamsetty p

•

Dec 14, 2021

excellent

By PUPPALA L U

•

Nov 27, 2021

excellent

By Sri P N R L C S

•

Nov 24, 2021

Thank you

By KALYAN B

•

Aug 12, 2021

Excellent

By Kavish J

•

Apr 18, 2021

excellent

By Amilton V B

•

Mar 12, 2021

Excellent

By Shubham N

•

Dec 12, 2020

Excellent

By 121910304062 g

•

Nov 29, 2020

excellent

By Pradeep S

•

Nov 27, 2020

very nice

By Shriram T

•

Oct 15, 2020

very nice

By Kratika H

•

Sep 29, 2020

Excellent