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Learner Reviews & Feedback for Machine Learning Foundations: A Case Study Approach by University of Washington

4.6
stars
13,485 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

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.

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1201 - 1225 of 3,140 Reviews for Machine Learning Foundations: A Case Study Approach

By Yuxi D

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Oct 30, 2015

It's a really good course! Easy to follow and instructors are nice!

By Dr. A K B

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Aug 16, 2020

This course is very useful to real time implementation of problems

By Lixuanwu Z

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Mar 29, 2020

Awesome and provides me some useful experience in machine learing.

By kattula n

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Apr 28, 2019

Concepts explaination and practical examples are optimal. Love it.

By Manjun W

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Jun 14, 2018

Very helpful. This is a good preparation for the advanced courses.

By Alfred D

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Feb 9, 2018

Very good introductory course , the examples were very interesting

By Xiuyuan C

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Jan 16, 2017

Definitely a good choice for entering the area of machine learning

By Daniel M

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Jan 11, 2017

Muy buen curso. Muy completo en la parte teórica y en la práctica.

By Memo R

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Oct 16, 2016

great class!!, I love how passionate you guys are about the topics

By Jiaqi L

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Apr 5, 2016

Very pratical and informative. Best Machine Learning course I had.

By Aarshay J

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Mar 9, 2016

Its a wonderful learning experience. I really enjoyed the course!!

By Tang K H

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Sep 26, 2015

I like this course and I like using Python and GraphLab Create. :)

By Viktor K

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May 14, 2021

Great Teaching!!! Easily Helps to understand the Machine Learning

By Karthikeya K

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Jul 25, 2020

Best way to learn about ML via creating case study while learning

By Prathamesh A

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Jul 20, 2020

Overall nice learning approach towards basics of machine learning

By Yevhenii S

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Jun 9, 2019

Very good course with solid coverage! BIG Thanks to the authors !

By Neeraj S

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Jun 8, 2018

I enjoyed the way the course was structured and examples provided

By Liwei L

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May 1, 2018

could be even better with a more comprehensive Python intro added

By Dongliang Z

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Jan 25, 2018

Excellent, really fun. I am going to the next course now. Thanks!

By Andrey N

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Jul 30, 2017

Great course! It can be even better if taught using scikit-learn.

By Amit K

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Aug 16, 2016

Sets a good foundation for getting started with Machine Learning.

By Ahmed M M

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Jun 16, 2016

awesome course , i loved machine learning because of this course.

By Pasquale G

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Feb 18, 2016

It's a great course. The adoption of ipython notebook is amazing

By Suresh A

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Feb 6, 2016

The presentation, the math involved and exercises were excellent.

By M L

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Nov 25, 2015

Absolutely amazing! The lecturers have great humor and knowledge.