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Machine Learning for Data Analysis に戻る

ウェズリアン大学(Wesleyan University) による Machine Learning for Data Analysis の受講者のレビューおよびフィードバック



Are you interested in predicting future outcomes using your data? This course helps you do just that! Machine learning is the process of developing, testing, and applying predictive algorithms to achieve this goal. Make sure to familiarize yourself with course 3 of this specialization before diving into these machine learning concepts. Building on Course 3, which introduces students to integral supervised machine learning concepts, this course will provide an overview of many additional concepts, techniques, and algorithms in machine learning, from basic classification to decision trees and clustering. By completing this course, you will learn how to apply, test, and interpret machine learning algorithms as alternative methods for addressing your research questions....



May 07, 2020

Clear and explanatory approach to the object. Instructors have great teaching transmissibility.


Oct 05, 2016

Very good course. I recommend to anyone who's interested in data analysis and machine learning.


Machine Learning for Data Analysis: 26 - 50 / 60 レビュー

by Jyoti P K

Sep 09, 2020


by Тефикова А Р

Mar 20, 2018

все супер

by Tejas G

Aug 31, 2020

nice one

by Artem A

Apr 14, 2016


by Steven L

Aug 30, 2017



Sep 25, 2020


by Keerthana G

Sep 22, 2020


by Mansi S G

Aug 25, 2020


by Mathilde v E

Jul 21, 2016


by Shreyans J

Jun 27, 2019

It is definitely a good one and easy to understand... What I mostly struggled was with the data sets which were hard to find... probably if some data sets would have been provided would have really helped - would have been easier to run the program through with multiple sets and see the best results across.

Essentially the major learning happens when you actually run it on your own (for which you may have to go back and forth with the instructors examples / teachings.

by Michael B

Jan 03, 2017

Excellent introductory course on machine learning focusing on simple linear and multiple regression, lasso regression and k-means clustering. A background in Python programming is useful but not required as the instructors discuss the techniques with annotated code examples.

by Christine R

Aug 15, 2017

I definitely appreciate this information on Machine Learning. And from an outsider perspective would say it is quite clear - when I put it into practice will see how it goes. I do like the video format and will say that through out the course the instructor

by Manikanta K

Apr 27, 2020

Since it is a part of a specialization, the topics start somewhere in between and is only recommended for those who have completed the previous courses with in these specialization.

by Mengyue S

Mar 22, 2016

More examples in coding and results are expected. So it is more convenient for students to compare different results and understand deeper


Jan 06, 2018

More Implementation oriented and less math

also contains distracting background videos when explaining important concepts

by Oriana A

Mar 21, 2017

Very good. I enjoyed doing it and learned a lot.

I would have liked that it had included r as one of the softwares.

by Leonardo A

Oct 31, 2016

Excellent course, some basic tecniques of Machine Learning are implemented in Python and SAS.

by Ivan C

Mar 03, 2016

I would like to have an opportunity to contact my reviews.

by Drew M

Oct 13, 2018

Learned some really useful ML models.

by Kailas R

Aug 18, 2020

Good course for beginners

by krushna l

Sep 14, 2020

it is very useful to me

by Lee X A

Mar 22, 2016

Disadvantages : Lacks Rigour, Lacks Support from instructors , Expensive , Peer review ( this is somewhat bad as most barely give any comments, though towards the end, reviews tend to be pretty good). *** DISCLAIMER *** I am not statistically significant as i only receive 3 reviews per week.

Advantages :Quick to earn cert, prewritten code available for easy use. Assignments on your own data. This is probably useful for people wanting to learn techniques for data analysis, who need not go too deep into the technique.

I would recommend this to people learning techniques for data analysis in various non-mathematical and non-statistical fields, though the content lacks rigour, and you need outside sources to help understand techniques.

This course IS NOT WORTH PAYING USD79, there are definitely other courses much more worth the money. You can audit it for free, if you do not want a cert.

by Dinesh B

Nov 05, 2017

The material is good but the functions should have been explained in more detail. There is kind of repetition of same thing. It should have given some more examples and changes in code to explain the different types of ways to apply same algorithm.

by Susanne W B

Mar 01, 2016

It was okay for an introduction to the methods, but I would have liked to learn about them in more details, i.e. the course was too short.

by Monika K

Apr 29, 2016

This level of detail was good for easier statistical concepts but there are much better courses on Coursera for Machine Learning