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

13,101 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


Oct 16, 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


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:

326 - 350 of 3,049 Reviews for Machine Learning Foundations: A Case Study Approach

By Vikram V

Sep 28, 2016

By Caio L F

May 24, 2018

By Marcio R

Feb 23, 2016

By Hamed A

Jul 17, 2022

By Deleted A

Oct 9, 2018

By Tim C

Dec 21, 2015

By Farooq M K

Oct 1, 2016

By 赵天琪

Aug 9, 2016

By Salman M

Jul 15, 2016

By Deleted A

Feb 27, 2016


May 16, 2017

By Simon A

Aug 8, 2016

By Mohammad M

Dec 25, 2015

By Gergő B P

Nov 1, 2021

By Gustavo K A

Jan 2, 2016

By Abhishek M

Aug 9, 2016

By Stefano T

Nov 30, 2015

By Samuel d Z

Jun 17, 2017

By Ghiath Z

Dec 12, 2015

By Govind R

Oct 26, 2020

By Kishlay K

Mar 2, 2021

By Rohan V

Feb 13, 2019

By Shouvik R

Nov 27, 2016

By Deepali S

Jul 13, 2020


Apr 7, 2021