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Вернуться к Machine Learning for Data Analysis

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

Оценки: 311
Рецензии: 66

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


4 окт. 2016 г.

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


6 мая 2020 г.

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

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1–25 из 64 отзывов о курсе Machine Learning for Data Analysis

автор: Mukkesh G

30 мая 2019 г.

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: Фаткулбаянов Т Р

7 февр. 2018 г.

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: Macarena E

19 сент. 2017 г.

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: Richard M

1 мар. 2016 г.

Not impressed with the teaching style.

Seems that lectures were being read and not taught.

автор: Γεώργιος Κ

4 июля 2018 г.

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: Adrielle S

6 февр. 2018 г.

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: Manoj K

22 февр. 2016 г.

I really liked this course. Concepts well explained. I was hoping for more practical exercises on different types of data sets along with how to improve model accuracy in various algorithm taught. concept such as pruning etc. were missing. But I am sure in future, we will have more on it. Thanks Professor.

автор: Павел Б

25 июля 2016 г.

It is very interesting, helpful, useful and wonderful course. Everybody who interesting in statistic must surely learn this course.

автор: Ruben D S P

29 июня 2018 г.

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: Kostas P

7 мая 2020 г.

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

автор: Bruno G C

5 окт. 2016 г.

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

автор: Edward M

25 июня 2016 г.

Good introduction with python example for famous algorithm such as random forest and k-mean

автор: Dmitry B

25 янв. 2018 г.

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

автор: Deleted A

28 июня 2016 г.

Option of learning both SAS and Python is great!

автор: Edita G

30 нояб. 2020 г.

Great course about machine learning methods

автор: Genara P

6 апр. 2017 г.

Excellet! I highly recommend!

автор: Jinbo C

7 янв. 2017 г.

easy to capture the concept

автор: Deleted A

7 сент. 2016 г.

short vedios and good ma

автор: thoai n

19 дек. 2019 г.

This is good course

автор: Karthik z

9 нояб. 2017 г.

Well structured .

автор: Yaman S

28 февр. 2016 г.

Excellent course

автор: Santhosh K J

25 февр. 2019 г.



10 июля 2020 г.

Good to learn

автор: Смирнов В Г

26 февр. 2018 г.

Great course!

автор: Thomas C K

11 окт. 2016 г.

Great Class!