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

4.6
stars
13,374 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.

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

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601 - 625 of 3,115 Reviews for Machine Learning Foundations: A Case Study Approach

By Hui Z

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May 4, 2020

Carlos and Emily provide excellent lectures. But it would be better if correct answers and detailed explanation can be provided for each assignment in the course

By Adarsh K

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Apr 10, 2020

course and the instructors were very good.

But figuring out how to install all the softwares in windows using wsl and copying files into that was a little tricky.

By Rohit k

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Jul 12, 2019

On behalf of our customers, we are focused on solving some of the toughest challenges that hold back machine learning from being in the hands of every developer.

By Ravi A

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Oct 27, 2016

Very good starter course for Machine Learning with enough practice examples. It was really helpful for me to understand what ML is and its real time application.

By Rafael A

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Feb 22, 2016

Excellent intro course. Emily and Carlos are really great. Very good balance of depth, practical application, and above all: intuitive, thoughtful explanations.

By Fahim K

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Oct 22, 2015

This course cover all the basic fundamentals require for Machine Learning.

Doing Assignment before this were never interesting. I am enjoying the assignment part.

By Diwakar S G

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Jun 6, 2020

This course is the best course that i have learnt till now. Wonderfully designed and presented.

Thank you to carlos sir , emily mam and entire team of coursera.

By Nagendra B R

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May 16, 2020

The best ever course a student can have on machine learning.really enjoyed the course,thanks for all the efforts put on this course by carlos sir ang emily mam.

By Weichang Z

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Jul 18, 2017

My favourite machine learning course for a starter, not only about these fundamental knowledge, the hands on practice of Python is really helpful for a beginner

By Andy C

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Feb 13, 2016

Best bang for your buck for getting hands on experience with popular machine learning techniques. Just the right amount of difficulty for an entry level course.

By Gireesan N P

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Aug 8, 2017

Amazing Course. Recommended to anyone with basics of Python. This is one which gives overall a good coverage on state of the art approaches to machine learning

By Ouanis S

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Nov 9, 2016

Excellent course, I particularly appreciate how concepts are introduced with examples to set the terrain for the consequent courses. Will definitely recommend.

By Robert H

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Sep 5, 2016

Great introduction to machine learning concepts. I look forward to the rest of the specialization and to developing some of my own methods and supporting code.

By Rishabh A

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Jul 16, 2020

The course was too good. I really enjoyed it & have learned a lot from this course.

Thank you, Coursera for letting me have this wonderful course.

Thanks a lot.

By Amandeep Y

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Nov 3, 2017

I really liked case study approach. I think one will be able to appreciate the application of the Machine learning along with the overview of the ML concepts.

By LEPAGE

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Mar 14, 2017

As a statistician, Excellent introduction to ML!! I can't wait doing the other specializations (regression almost done, clustering and classification on-going

By Purbasha C G

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Dec 4, 2016

Great Introduction to machine learning. Found the Turi APIs and iPython Notebook approach very effective in getting acquainted to machine learning algorithms.

By Ramesh

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Sep 21, 2016

Really good explanations of the topic with practical examples and implementations. Its like a quick recap of important concepts in ML. I would recommend this.

By Kurt D W

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Mar 10, 2016

Great introduction to get familiar with the different concepts of machine learning especially when you have no ML background at all. Surely recommended by me.

By Arun M

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Sep 15, 2019

Excellent course. Helpful to start learning Machine Learning courses. As the course is practical oriented, helps to learn many python libraries used for MI.

By Alejandro M

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Nov 13, 2016

Excellent approach to get started with Machine Learning, good teachers that make entertaining to follow the lessons, thanks for the good work you put in it!

By Abhijit K

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Jun 2, 2016

Very nice way of teaching such a difficult subject. I like both the instructors. Assignments are bit easy though and must have been on open source software.

By Chase M

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Jan 21, 2016

Very approachable method that gets more in depth at a good pace. The later courses in the specialization dive deeper and get into the more complicated math.

By Jaganmohan R N

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Oct 27, 2015

Very well organized and very interesting. Increasing the levels of curiosity and enjoyed the course to full extent. Thank you for offering the Great Course.

By Jacek K

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Sep 6, 2020

Very good introduction to machine learning, along with some required python basics, good to pickup by any person, even without computer science background.