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

4.6
stars
11,675 ratings
2,799 reviews

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

PM

Aug 19, 2019

The course was well designed and delivered by all the trainers with the help of case study and great examples.\n\nThe forums and discussions were really useful and helpful while doing the assignments.

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

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51 - 75 of 2,712 Reviews for Machine Learning Foundations: A Case Study Approach

By john p

May 13, 2016

No Open Source Libraries, this course is not educational; it is a sales pitch to use their expensive software. Good luck having an employer pay this amount of money for software when they can hire employees that can use free open source libraries.

By Christopher W

Oct 15, 2015

The fact that the class uses GraphLab instead of pandas/numpy/sklearn should have been stated up front

The course felt like an advertisement for the professor's toolkit

It was very disappointing that the equivalent standard workflow was not supported

By Amirhossein f

Mar 14, 2020

The instructors need to specify that you can run this course specialization using MAC or Linux only. I have wasted my time for the past 3 weeks trying to figure out how to run the Sframe or Turi using windows and could not find any solution.

By Natalia Q C

Jul 25, 2019

The instructions to download GraphLab don't work and even when you sign to use the AWS platform the instructions are also old and I haven't been able to start any of the assignments because of that! I want MY MONEY BACK!!!

By Alejandro

Jun 13, 2016

Shame that it was not possible to progress with this course without using graphlab which the creator of this course himself created. Please see the course as just a training sales promotion for his ML application.

By Toma K

Jun 11, 2019

Warning! I paid for the specialization and now it tells me that the course ended 2 months ago!! i can't complete quizes which is why i paid!!! no options available to contact support.... no refund available....

By Pablo S

Jul 22, 2019

I should have read the negative reviews before wasting two full days trying, and failing, to install the required software. I urge anyone reading this to avoid this course and look for alternatives.

By Xing W

Jul 03, 2016

I was expecting to solve problems using more open-sourced package. Unfortunately, I feel this series of courses are more of an advertisement for the instructor's software company.

By Eduardo R R

Sep 23, 2015

This course rely on commercial library. I am sorry, I don't believe the convenience of a commercial library is good for your learning. You may end up locked in.

By Dmitri K

May 27, 2016

The whole course based on some proprietary software. In general, it seems that the main goal of the course is promote that software.

By sravan

Oct 13, 2016

there is no proper documentation.

at least there should be some clear instructions for first program

By Mario L

Nov 24, 2015

I dont like the tools they used, it seems like a promotion for their company.

By Lester L

Mar 21, 2020

Not made for Windows, you need a linux or mac VM to apply this course.

By Tim B

Jun 04, 2019

Complete waste of time until it is written using open-source packages.

By Phillip B

Sep 25, 2015

Would have greatly preferred if open source tools were used.

By Chandrakant M

Sep 06, 2016

I felt that I paid for demo of the Dato/Turi.

By Nitin K

Sep 12, 2019

Not good support to learning process.

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 J A 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 akashkr1498

Jan 18, 2019

lacture was good but one point i want to share to you don't use rare tools for assignment personally i faced lots of problem while installing graphlab better to switch to some common tools like sklearn python platform .

By Yuvraj S

Feb 01, 2019

It is a good course if we take into account the foundational part. But since only one library has been used to solve the issues, one does not explore and write their own functions.