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

4.6
stars
13,509 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 17, 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 20, 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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3076 - 3100 of 3,150 Reviews for Machine Learning Foundations: A Case Study Approach

By shanky s

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Apr 26, 2021

I thought that indepth will be taught and enrolled for this course, but unfortunately its only basics. I wasted my enrollement

By Simone V

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Apr 21, 2022

It started nice but there are some basic aspects, like installing Turi Create, neglected. I had to withdraw from the course.

By Piotr T

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Oct 6, 2015

it's rather a course on using API of proprietary software with very very basic background on the actual math underneath

By A C

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Jun 21, 2023

Needs to be updated. Graphlabs seems impossible to install. Needs an older version of PIP, non compatible with M1 Macs

By David F

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Dec 2, 2015

I didn't like the python environment, I thought it will be more like Ng's course. Nice explanations, but for amateurs.

By Patryk H

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Oct 14, 2015

Due to many technical issues with GraphLab lib I have to reduce acitivity in this curse for only video viewing :(.

By Edgar

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May 29, 2020

Course videos are outdated and requires time to investigate and research. This causes wasted time and effort.

By David H

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Oct 31, 2015

Very, very high altitude introduction presented in a seemingly confused way with a lot of product placement.

By Zuozhi W

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Feb 8, 2017

TBH this class's experience is not good. The lecturers seem unprepared and they talk very repetitively.

By Suhasini L

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Sep 4, 2020

Not given details like what is a vector? people from non technical backgrounds will have tough time

By ashish s g

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Feb 15, 2017

Very good course material. However, Graphlab is no longer free to use for commercial purpose.

By Mark F

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Dec 19, 2015

This course is to much about graphlab and not enough about the mechanics of machine learning.

By Najmeh R

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Oct 4, 2016

The subjectes are not learnt deeply and precisely. Too summarized and vague!

By tiafvoonug k x

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Jan 6, 2016

As a non programer, or mathematician, this course is too hard to follow.

By Daniel H

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Dec 1, 2022

Did not work on Mac OS X ARM64 also uses out of date python version

By sumi d

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Jun 6, 2020

They Don't tech the mathematics behind the machine learning.

By Satyam N

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Mar 26, 2018

This course doesn't give any insight about the algorithms.

By Paolo G

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Apr 18, 2021

This course has no value!!! it's using obsolete tools.

By Gencho Z

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Oct 1, 2022

Wors ML course I've had on Coursera so far.

By Chenyu L

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Nov 8, 2023

not friendly to windows users

By Hubert K

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Mar 1, 2025

old lib dont work in 2025

By Mohamed T K

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Jun 26, 2020

Too hard

By Richard M

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Jul 4, 2021

I would avoid this course. The course structure is badly organised and hard to follow, the material covered is lacking in detail on key underlying concepts that are key to learning what you're doing and the notes provided do not provide key information that would let them be used as reference material for you to go back and review.

But - much more importantly - the course notes and information have been written using an old, out of date, library, while the tests and some of the material refers to a newer library that is not a direct replacement. As a result, many of the instructions and guides don't work at all, or are incredibly hard to understand with the new model.

Finally, also as a result, many of the test question's answers are wrong - when you do the questions using the new library you get an answer that the automatic grading says is wrong - even though it is correct.

And there is no help in the dicusssions from moderators.

So while this may have been a passibly acceptable course at one time, it is now basically a frustrating, bi-polar mess, with no help provided to guide you.

By Raza K

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Apr 6, 2020

I have a few concerns regarding this course. First of all the instructor strongly suggested that we should use python and turicreate package. I had several difficulties in installing turicreate on my mac. There was no help avaliable on the forum in this regard. Finally, I ignore the instructions and downloaded anaconda and then downloaded turicreate.

But it turns out that the instructors are not using turicreate in lectures but graphlab package. Moreover, the instructors using python 2.7, which has a different syntax than python 3.

This made learning much harder and frustrating.

By vedant m

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Jun 12, 2021

i was very excited to start this course but the turicreate causes a lot of problems in your pc as it requires wsl to be installed(whenever i try to load data into sframe for some reason my pc doesnt allow it to read those files in the virtual environment and many technical issues such as that).. i found all of this very frustrating and im extremely disappointed. I tried to fix those technical issues through internet but to no avail. im extremely disappointed and i will unenroll from the course unless they come up with another way for implementing python codes