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

4.5
stars
3,149 ratings
601 reviews

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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401 - 425 of 592 Reviews for Practical Machine Learning

By Nicholas T

Jul 3, 2020

Very good course. Fast paced and a lot of self study required to fully understand some of the nuances of the R (if you're not familiar with the language).

By Eric L

Jun 2, 2016

Great course, very high paced with a lot of information. would have been great to add two more weeks and another project to use more machine learning

By Igor H

Sep 10, 2016

Rather basic, nevertheless a good introduction to the topic of machine learning with R. Mostly concentrated on applications of the R caret package.

By Lee G

Sep 22, 2017

A very good starter course on Machine Learning in R with great links to various resources that students and delve deeper into the various topics.

By Yashaswi P

May 24, 2020

Good Course the covers a lot of practical aspects and relevant to the real world solution.

Good References and Learning Materails are available

By Ann B

Sep 6, 2017

Good class to get the basics of Practical Machine Learning. This course is best taken as a part of the data science series from John Hopkins.

By Gabriela C V

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

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

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

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

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

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 D

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

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

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 Sulan L

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

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

Aug 14, 2016

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

By Jeffrey E T

Mar 28, 2016

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

By BIBHUTI B P

Jul 24, 2017

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

By João R

Aug 20, 2017

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

By Daniel R

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

Jul 26, 2018

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

By Greig R

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

Jun 28, 2018

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