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
13,527 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

BL

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

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.

Filter by:

876 - 900 of 3,156 Reviews for Machine Learning Foundations: A Case Study Approach

By Gillian P

•

Feb 4, 2017

Good material. I'd prefer the course going without graphlab though. I hope course 5 will be produced one day.

By Tianyu Z

•

Jun 14, 2016

awesome course, a really good course to start your data science class. the software is a little uncommon tho.

By Yoga N

•

May 31, 2016

The trainers are amazing..! The step by step approach with the business use case helped me understand better.

By Sudip C

•

May 3, 2016

Very simple to understand, detailed. Best for a newbie. Graphlab is awesome. Loved the "Case study" thinking.

By KONDAVEETI S

•

Jul 10, 2021

The course was really helpfull for my further studies in the field of ML.The insrtuctors were really helpful

By Budi S

•

May 9, 2020

I like how both professors teach this fundamental ML concept and practical. I'll try to do that in my class.

By Niyati M

•

Apr 13, 2017

Great one for people who need to implement it for websites and are not concerned about the underlying stuff.

By Claudia V A B

•

Apr 14, 2016

Excelent course that gives you a global vision about actuals machine learning probles and how to solve them.

By Moises V

•

Mar 23, 2016

Great introduction to Machine Learning, I'm Highlight motivated by this course on pursue the specialization.

By Usman A

•

Oct 22, 2021

Excellent course for beginners. Mathematical concepts were rigorous and provided an in depth understanding.

By Rizwan A S

•

Aug 8, 2019

Very easy to understand and get familiar with the basic of machine learning through the practical examples.

By Jayaganesh G

•

Dec 19, 2017

Learning from real world problem than a toy problem. Very different from others and much practical. Thanks.

By Suresh K

•

Aug 12, 2017

Very practical case studies to learn the core concepts of machine learning. Most recommended for beginners.

By santosh k

•

Sep 30, 2016

The course is very intuitive and very explanatory. This is very help course to begin with Machine Learning.

By Pavel K

•

Aug 5, 2016

A very clear and straightforward course giving a foundation for the following learning of Machine Learning.

By Damian T

•

Feb 24, 2016

Great course! It wets your appetite for a more in depth look at the various techniques to machine learning.

By Bhawani S L

•

Nov 3, 2015

Very good course to start Machine Learning Basics. Excellent coverage of practical programming assignments.

By Dr. M A H

•

Jun 7, 2020

Excellent course materials

Good data collection

Good delivery of lecture notes

Five stars for all hospitality

By Junfeng D

•

May 20, 2018

very great course in a case study approach, you will be familiar with all basic algorithms and ML methods.

By 易灿

•

Apr 16, 2016

Awesome, very very useful, and intuitive! Hope teachers can introduce some books or papers for us to read.

By De.Sambath M

•

Mar 13, 2016

Excellent. Went through the introduction videos and course material. Great one. Thanks for publishing it .

By Hugh A

•

May 13, 2022

really good intro to the fundamental principles of Machine Learning ... also ... it really stretched me !

By Muhammad R C S

•

Dec 26, 2020

A complete fundamentals of understanding how machine learning works! Valuable to develop my career ahead

By Jason S

•

Oct 30, 2019

This was exactly the combination I needed of concept, use case, interpretation, and hands-on application.

By Noam K

•

Apr 2, 2019

Nice overview, the case study approach is very useful as well as the actual python notebook assignments.