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Learner Reviews & Feedback for Practical Machine Learning by Johns Hopkins University

4.5
stars
3,239 ratings

About the Course

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation....

Top reviews

MR

Aug 13, 2020

recommended for all the 21st centuary students who might be intrested to play with data in future or some kind of work related to make predictions systemically must have good knowledge of this course

AD

Feb 28, 2017

Issues of every stage of the construction of learning machine model, as well as issues with several different machine learning methods are well and in fine yet very understandable detail explained.

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426 - 450 of 615 Reviews for Practical Machine Learning

By Gabriela C

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Dec 14, 2020

It's harder than the previous one. it would be nice to update some the quizzes as they are based on older versions of R Studio libraies.

By Hernan S

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Dec 13, 2016

The quiz should be constructed in a way that depends less on the version of the libraries used. The rest of course was excellent.

By Jakub W

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Sep 24, 2018

Vary practical approach, almost no theory or in-depth explanation of the subject, but a lot of focus on applying ML in practice

By Md F A

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Aug 14, 2017

To me with this course, the best learning aspect is the final project; how to use Machine Learning Algorithms on data analysis.

By Rhys T

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Oct 10, 2017

Good course, some aspects of the assignment were a bit beyond the scope of what the course teaches but overall I learnt a lot.

By Níck F

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Sep 27, 2016

Was pretty good, but quite short and some assignments did not align as well with the lecture material as they could have.

By Michael O

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Jan 10, 2020

This is a great course, but it would be good to see it updated to use the newer evolution of the caret package, parsnip.

By Tongesai K

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Feb 8, 2016

Very good course. I am very knew to this topic but am sure will find a lot of application in my speciality - geophysics

By Kevin S

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Mar 2, 2016

Good introduction to machine learning, might suffer a bit from trying to cover too much ground in such a short time.

By SEBASTIAN E C

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Aug 17, 2021

Maybe final review must be verified by an expert, also the kind of data to analyse must be change over the time.

By Sulan L

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Nov 19, 2018

I hope we can have more détails in this cours and to see how to use the algorithms for the big data. Thank you.

By A. R C

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Oct 20, 2017

I enjoyed it but it needs indeed to deep into many concepts, which are just briefly named during the course.

By Marcelo G

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Aug 14, 2016

Great course, very demanding, but it could use more reading material, ebooks instead of links on video.

By Jeffrey T

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Mar 28, 2016

Good overview of available techniques and the Caret package. Will get you started in machine learning.

By BIBHUTI B P

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Jul 24, 2017

This was a superb module which created a deep learning insight within me focusing on future technology

By João R

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Aug 20, 2017

Got confused how to perform cross validation and when. Other than that, very practical. Great job.

By Daniel R

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May 14, 2016

The course is really great, however it should last a little longer, 4 weeks is hard to accomplish

By César A C

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Jul 26, 2018

Very interesting course. May be a little bit harder than the previous ones but it could be done.

By Greig R

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Nov 13, 2017

Good course, I learnt a lot. It does need to be updated with more modern versions of software.

By Pieter v d V

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Jun 28, 2018

Very quick overview. If you really want to know something about it read the reference books.

By Guilherme C C

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May 18, 2016

Title says everything. Practically and basically no theory explained. Good course though.

By Carlos C

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Aug 12, 2017

Excellent content so I give 4 starts. I stat less because the trainer speaks too fast.

By carlos j m r

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Oct 5, 2017

I thought there were Swirl practice as other courses, however this course is very good.

By alon c

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Mar 10, 2016

Great Course, will be nice to have more projects to see how it goes with different data

By Anant S

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Jun 30, 2017

good course for initial understanding of machine learning. SVM can also be included.