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Avis et commentaires pour d'étudiants pour Apprentissage mechanique pratique par Université Johns-Hopkins

4.5
étoiles
3,062 évaluations
580 avis

À propos du cours

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....

Meilleurs avis

MR
13 août 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
28 févr. 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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151 - 175 sur 570 Avis pour Apprentissage mechanique pratique

par Alfonso R R

13 nov. 2018

Hands on course. Loved it. It goes a little bit fast, however, the content is ambitious.

par Brian G

16 août 2017

Great course. Mechanics of the final assignment are more difficult than the work itself.

par Sean D

10 juin 2020

Really liked Dr. Leek's talks, and the subject matter was interesting and kind of fun.

par Konstantin

2 mars 2020

Excellent course. Lots of exorbitantly useful knowledge. I`ve been lucky to start it.

par Donson Y

4 sept. 2017

This is a fantasy course to know that how to build your first machine learning model.

par Jorge M A A

13 avr. 2016

I enjoyed a lot this module, I'll use at my daily work some of the features I learned

par Premkumar S

16 mars 2019

Great course and farily challenging exercises! Thank You for putting this together!!

par Sai S S

17 juil. 2017

Great course. Ways to curb plagiarism & cheating needs to be revisited by your team.

par Thet P S A

21 août 2020

It supports a lot in my thesis. Thank you, lecturers, at John Hopkins University.

par Mary

19 août 2019

Very informational with good variety of code to take back and apply to projects.

par Nikhilesh J

2 mars 2018

Provides a quick and dirty look at Machine Learning. An easy way to get started.

par Jeffrey M H

10 juin 2019

So far, one of the most fulfilling courses in the Data Science specialization!

par Ajendra S

7 nov. 2017

This a good course, giving you the inside of the data science problem solving.

par Lei M

23 août 2017

This course is demanding, but I feel my own progress which is very fulfilling.

par Johan V M

21 août 2020

I loved this course. I will absolutely take more courses on Machine Learning.

par Forest W

9 janv. 2018

Much Better than the previous courses ( Regression and Statistical Inference)

par Chris H

23 mai 2016

Great course. I really enjoyed working on the prediction project at the end.

par Marcus S

11 févr. 2016

Great introduction to the subject with good classification examples using R.

par Gayathri N

21 sept. 2020

Wonderful foundational course to understand the basics of machine learning.

par Sarah S

31 mai 2017

I enjoyed detailed information and was very straight forward to understand.

par SATHYANARAYANAN S

10 sept. 2017

Very good for anyone wanting to get into the field of Data Science using R

par Sandro G

13 oct. 2017

I have learnt a lot of thing and very happy to have followed this course

par Camilo Y

14 mars 2017

This course is a good introduction to machine learning algorithms with R

par Massimiliano F

17 févr. 2017

In my opinion, the best course of the entire Data Science Specialization

par Diana S

10 févr. 2016

Thank you son much!!!!

I really like the course.

It help me in my job =)