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
13,186 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

SZ

Dec 19, 2016

Great course!

Emily 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.

PM

Aug 18, 2019

The course was well designed and delivered by all the trainers with the help of case study and great examples.

The forums and discussions were really useful and helpful while doing the assignments.

Filter by:

401 - 425 of 3,054 Reviews for Machine Learning Foundations: A Case Study Approach

By Aniket R

Feb 6, 2016

By ROBIN S 1

Dec 10, 2020

By Alessio D M

Dec 7, 2015

By Lin V

Feb 20, 2016

By Cristina E

Feb 12, 2016

By Hossein N S

Feb 9, 2016

By Ethan G

Nov 22, 2015

By PRAVEEN R U

Aug 23, 2018

By SANDEEP

Jul 27, 2018

By Carlos A M

Jan 18, 2021

By Adrian L

Jul 10, 2020

By Lokesh K

Jan 26, 2019

By Ramesh K

Feb 8, 2016

By DURGESH G

Jun 21, 2020

By ANIMESH M

Jun 8, 2020

By Muhammad H T

May 4, 2020

By Rania B

Jan 6, 2019

By 黄怡

May 29, 2018

By Olga V

Jul 7, 2017

By Eik U H

Jun 27, 2017

By Lucas d L O

Aug 9, 2016

By Guillermo R

May 13, 2018

By Kan B

Oct 24, 2016

By jeevanjot s

Oct 29, 2018

By Pranav V V

Oct 15, 2017