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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.

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851 - 875 of 3,156 Reviews for Machine Learning Foundations: A Case Study Approach

By Jaime M

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Oct 18, 2017

This brief introduction to ML techniques is really awesome. I have learned the intuition behind each ML algorithm.

By Stéphanie G

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Jul 13, 2017

Amazing course, great structure for the first course of the specialization. Can't wait to start the second course!

By Anjali C

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Nov 20, 2015

Learned a lot !!

Looking forward to other courses in specialization :)

Appreciate the enthusiasm of both professors.

By Rifki W

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Jun 25, 2020

its a great start for learning ML. You will learn the basic and intermediate ML. Thank you Washington university.

By Ahmad A

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Feb 11, 2017

I really enjoyed the course. I am interested to continue in this specialization and conduct the Capstone project.

By David P

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Feb 8, 2017

Amazing introductory course! I only wish that Coursera was still offering courses 5 and of the specialization :(

By Javier P

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Oct 28, 2016

It was a great course. I learned many things during this course. Btw, the teachers are really cool... super cool.

By S P

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Mar 2, 2016

Excellent course - very informative. Thanks!

Some areas could do with a little more details just as deep learning.

By ANGELICA D C

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Sep 1, 2020

Hubo una ocasión en que no se nos proporcionaron los datos correctos de un set de datos, fue en el último curso.

By Gowtham A B

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Nov 22, 2019

Very good course to kick start in machine learning domain. The assignments and course contents were really good.

By Victor S

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Dec 7, 2017

It was fun putting the theory in to practice and 'play' with the models and data to udnerstand what is going on.

By Balakrishnan

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Nov 27, 2015

Like the approach of introducing the subjects with real use cases and have a detailed session on future courses.

By MIGUEL A M B

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Nov 12, 2022

una muy buena aproximación para manejar python, aprender los fundamentos del machine learning y deep learning.

By Daniel R

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Oct 8, 2020

Great course on Machine Learning guided by great teachers that will ensure your learning experience in Coursera

By Kishan P

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May 18, 2020

Awesome Course both of the instructor is very good in his teaching and very friendly teaching, well structured.

By SOUVIK D

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Nov 5, 2018

awesome course. 100% recommended for beginners. I just loved it. Thanks to Coursera for providing such courses.

By Rashi K

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Dec 13, 2015

It was pretty basic but worth what was needed for a head start in machine learning. I enjoyed the course a lot.

By abdulkarim k

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Mar 26, 2020

Thanks Carlos and Emily very much for this wonderful course. Your way of presenting the topics is very cool :)

By sohan l b

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Mar 4, 2019

This course is good for beginners.This course covers hands-on as well as Basic theory and their applications .

By James Z

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Feb 29, 2016

A great lesson to learn about machine learning. Two teachers are very funny and the quizzes are not very hard.

By K C

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Jan 14, 2021

Good introductory course. Gives a flavor of the various topics and sets you up for the next in-depth courses.

By Arindam M

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Mar 28, 2019

It was a really nice course. It will be further helpful if the regression algorithms are discussed. Thank You

By Rahul K

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Sep 11, 2018

The lecturer's teaching is well organized and presented, which helped me to accept the new knowledge quickly.

By Ferdinand K

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Feb 17, 2017

Good stuff so far. Great examples, easy to follow. Speeding up the lectures by 1.25 or 1.5-fold helps as well