Chevron Left
Вернуться к Machine Learning for Data Analysis

Отзывы учащихся о курсе Machine Learning for Data Analysis от партнера Уэслианский университет

4.2
Оценки: 220
49 рецензий

О курсе

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....

Лучшие рецензии

MG

Jan 16, 2019

A good introduction to Machine Learning. Makes me curious to know about the methods that are available outside of this course. Great material as usual.

BC

Oct 05, 2016

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

Фильтр по:

1–25 из 47 отзывов о курсе Machine Learning for Data Analysis

автор: Фаткулбаянов Т Р

Feb 07, 2018

The course was indeed pretty interesting, I've learned a lot of new things (and got to learn how to do a little bit of coding using Python). The only thing I would recommend is to add some more datasets, because even though it's pretty easy to find some datasets on the Internet, I think 3 out of 5 suggested datasets were extremely difficult to figure out and were much more complex than the other two.

автор: Mukkesh G

May 30, 2019

A good introduction to Machine Learning. Makes me curious to know about the methods that are available outside of this course. Great material as usual.

Update After actually studying Machine Learning for months: A pretty intro to the world of ML. After learning the math behind it and other algorithms, I can say that this specialization is pretty much just the Statistical interpretations of your analysis (explained with the implementation of some powerful yet basic algorithms without really getting into the Hard Core math behind it)

автор: Santhosh K J

Feb 25, 2019

GREAT KNOWLEDGE

автор: Aurimas D

Feb 01, 2019

Absolutely unbalanced course. Course has 4 different topics, but it does not explain well non of them. In reality whole course should be dedicated for at least one of provided topics.

автор: Ponciano R

Jan 23, 2019

It´s a good course but it does not goes deep enough in the examples and techniques.

автор: Drew M

Oct 13, 2018

Learned some really useful ML models.

автор: Γεώργιος Κ

Jul 04, 2018

A must to do introductory course. I will never regrett taking that valuable course but I have to say that some improvements would make it much better. The theoretical background is too short and the proffesors seem to spend more time to describe simple functions like saying put there an ('underscore', 'parenthesis') than seting the reasons of doing that and what are the targets of the programmes. Any way all of these problems and maybe some more are not a reason for someone who wants to start machine learning to not participate in that course especially if he is a pythonist.

автор: Ruben D S P

Jun 29, 2018

Great classes. It is the beginning to machine learning, and you can try more classes about it. You can find many job about it.

автор: Тефикова А Р

Mar 20, 2018

все супер

автор: Остроухов М Н

Mar 06, 2018

Unfirtunately superficial and outdated view on the subject.

автор: Смирнов В Г

Feb 26, 2018

Great course!

автор: Adrielle S

Feb 06, 2018

Excelente curso. Explicações didáticas com exemplos reais implementados e detalhados em python. Descrição muito boa das aplicações das técnicas apresentadas bem como de suas limitações. Parabéns para as professoras por esse excelente curso e muito obrigada por nos disponibilizar este trabalho maravilhoso no Coursera.

автор: Dmitry B

Jan 25, 2018

There is some problems because of changes both in SAS and Python after creating the course

автор: ADITYA Y P

Jan 06, 2018

More Implementation oriented and less math

also contains distracting background videos when explaining important concepts

автор: karthik

Nov 09, 2017

Well structured .

автор: 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.

автор: Macarena E

Sep 19, 2017

I enjoyed this course a lot. It's easy and I've learnt what I need to apply the machine learning techniques. Easy and simple. You don't need to be a mathematician.

автор: Vanessa Q M

Sep 05, 2017

It goes over and over about the adolescent examples, which makes it annoying. The quality and production of the video is bad. Why to use moving scenes in the background (like the horses or the highway)? That's distractive and takes the focus of the content, better to use a blackboard.

автор: Steven L

Aug 30, 2017

Good!

автор: 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

автор: Genara P

Apr 06, 2017

Excellet! I highly recommend!

автор: 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.

автор: Jinbo C

Jan 08, 2017

easy to capture the concept

автор: 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.

автор: Karthick K

Dec 12, 2016

Course could be better