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

4.6
stars
13,372 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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76 - 100 of 3,115 Reviews for Machine Learning Foundations: A Case Study Approach

By Vishok G

Oct 12, 2020

IF you are a beginner who would like to take up a job in a Data Science related field, read on:

The packages used here are not listed in a single job requirement in Angel, Glassdoor, etc. I know they said use the tools you want to, but most people taking up courses like this or similar are people with none or limited experience in Machine Learning. Rather than promoting tools created by the professor (Turi; Read the Wikipedia page, it seems like an advertisement) they need to use tools that are widely used in the industry.

(Though Turi has been acquired by Apple, the scope is very limited)

Furthermore, due to lack of proper support and solutions on sites like Stack Overflow, it gets harder for a person who lacks programming experience to debug if any problems arise

**THE BIGGEST ISSUE: Turi is NOT SUPPORTED on Windows!** I had to use a virtual environment in Ubuntu Terminal. (I may be wrong with the exact wording) For finding out how to use the package read this:

https://blog.usejournal.com/installing-turicreate-on-windows-10-534e147a4792

(Funny thing, the author of the page actually wrote "If you are taking the Machine Learning Foundations: A Case Study Approach", meaning someone would rarely use it for anything else IF they do)

Concept Explanation was good, but the above point was a major disappointment because I had to learn packages like Pandas and Scikit-Learn (Any job listing on Machine Learning using Python would list these as a MUST requirement. Besides, the support available on Stack Overflow is huge) after learning a package I would never use in my job.

So my suggestion is if you don't mind learning Turi and would like a surface level explanation of the concepts, go on.

By Mihir I

May 13, 2020

Extremely disappointed with the quality of the teaching content. There is a major disconnect between the materials presented in the videos and quizzes. While there is a warning that there has been a shift from graphlab to turicreate, there is no way to assess the impact on additional effort required to fill in the gaps. In fact, one of the instructions in the week 2 programming assignment is outright wrong so you will be able to pass quiz. The discussion board is tough to navigate because of the subject heading are cryptic e.g. Need help, Error, etc. As a result one has to sift through many post to get an answer. Compared to other offering on Coursera, It is not worth paying for this course.

By Peter F

Mar 30, 2020

This course would be okay if it weren't for turicreate, a Python package that's supposed to simplify things. If you have Linux or a Mac, it will do just that, but if you have Windows steer well clear of this course. The lecturers haven't considered the possibility that anyone might not have Linux or a Mac. All the faffing around getting turicreate to work (I did it once and I'm not doing it again) wasn't worth my trouble so I ended up guessing the answers to the quiz questions (you're allowed three attempts every eight hours) just to get this course out of the way. I'll use something actually accessible for the remaining courses, namely R.

By David Y

Oct 3, 2021

Content is not updated, 3 years old, they tell you that the course will cover TuriCreate but all the videos show GraphLab content. Syntax is for Python 2, and although this last one is not supercomplicated it shows the lack of interest for the students from the University because after 3 years they haven't updated the content!

Go to the forums and see how many people are stuck in Week 1, just trying to install the tools requested, which require plenty of workarounds to be installed in windows.

By Rithik S

May 26, 2020

The files that are given in readings are unable to open and turicreate cannot read that files also. I cant complete my assignments without reading those files. They haven't given any detailed explanation about how to read those files. In videos they had explained through csv files but in assignments they had given sframe file which are unable to read

By Yakubu A

Dec 23, 2020

The learning tools and environment is not friendly. The use of graph lab seem outdated since python 3.7 does not seem to support the module. I suggest the course be reviewed. Python 2.7 seem to be going out of the system so something should be done about this

By Vincent B

Jun 30, 2023

TOTAL GARBAGE.

COURSE IS OUTDATED AND NOTHING WORKS.

I SPENT HOURS TRYING TO INSTALL AND SETUP THE REQUIRED SOFTWARE ONLY TO FIND OUT IT'S OUTDATED AND NO LONGER SUPPORTED.

IF YOUR NOT GOING TO KEEP THIS COURSE UPDATED THEN TAKE IT DOWN.

By ye

Jan 31, 2021

The course is limited to use special package - turicreate, sframe, no detailed explanation of how to install that. Packages used are very out dated

By Jitendra S

Apr 29, 2016

Dato tool does not even install properly.. so n´makes no sense to continue with the course. The support team fail to help in installing ... :-(

By Ashutosh N

May 30, 2020

The course is explained using turicreate , which does not work in windows properly. It should have been explained using open source libraries.

By Krupesh A

Feb 15, 2019

Uses very old versions of libraries. Many students are facing issues which remains unsolved. Not recommended to pursue it.

By Rolando J R I

Feb 14, 2022

They are using python 2, It is very out-of-date.

After the first week, I count not pass the first test...

By Shreyash N S

May 20, 2020

graphlabcreate creates many problem while working..it should be changed

By Japman S

Jun 6, 2020

Based on Python 2 libraries not working on python 3. Obsolete Course

By YM C

Sep 6, 2019

Too old, bad packages, not much to learn. too basic.

By Darren R

Oct 13, 2015

Thoroughly disappointed to see this course based on

By Kaushik M

Apr 30, 2016

Too many videos and not cluttered assignment codes

By D. F

Feb 2, 2021

Out of date material. Poor instruction

By Rohit

Apr 19, 2020

This course is pretty good for beginners. All domains are explained briefly as an introduction. The best part about this course is very good hands-on sessions which are really helpful to understand concepts. The course is not very detailed but it's very good to start with. Looking forward to quality courses ahead in this specialization.

By Shibhikkiran D

Apr 13, 2019

This is course is very informative for a beginner. It helps you to get up and running quick provided you have little basics on Python. You should( sideline on your own interest) also pickup Statistics/Math concepts along each module to make a rewarding experience as you progress through this course.

By Diogo P

Feb 15, 2016

With a funny and welcoming look and feel, this course introduces machine learning through a hands-on approach, that enables the student to properly understand what ML is all about. Very nicely done!

By Karthik M

Dec 27, 2018

A good course to understand the basics of Machine Learning. The only issue is the use of Graphlab library. Since it only works on Python 2.7, it is not convenient for people who prefer Python 3

By Alexandru B

Jan 21, 2016

Great course. Very informative and inspirational. I got tons of ideas from it! Thank you

By Mallikarjuna R V

Jan 17, 2019

Wonderful opportunity to learn and execute hands on coding of Machine Learning. The amazing task that Machine Learning methods and algorithms does behind scene is understood for the following cases / intelligent applications:

1. Regression (e.g. Predicting House Price etc.)

2. Classification (e.g. Product review sentiment, Spam detection, Medical diagnosis etc.)

3. Clustering and Similarity (e.g. Grouping news articles)

4. Recommender (e.g. Amazon personalized product recommendations, Netflix personalized Movie recommendations etc.)

5. Deep Learning and Deep Features (e.g. Google image search, Image-based filtering etc.)

The main challenge for me was to code using “Python3, Pandas and SciKit-Learn” instead of “Python2, GraphLab Create and SFrame”. I am now confident to develop intelligent applications based on Machine Learning. Thanks to Professors (Emily and Carlos) and to Ashok Leyland-HR for giving me this opportunity.

By Sundar R

Aug 19, 2020

The teaching is of good quality and the lectures are easy to follow along. The only downside I thought was week 6 where I felt the topics weren't covered in enough detail in order to clear the quiz. Lastly, very disappointed by the exclusion of courses 5 and 6 which would've made this specialization a complete package.