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Machine Learning for Data Analysis(으)로 돌아가기

웨슬리언 대학교의 Machine Learning for Data Analysis 학습자 리뷰 및 피드백

313개의 평가
67개의 리뷰

강좌 소개

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....

최상위 리뷰


2017년 9월 18일

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.


2016년 10월 4일

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

필터링 기준:

Machine Learning for Data Analysis의 65개 리뷰 중 1~25

교육 기관: Mukkesh G

2019년 5월 30일

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)

교육 기관: Фаткулбаянов Т Р

2018년 2월 7일

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.

교육 기관: Macarena E

2017년 9월 19일

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.

교육 기관: Richard M

2016년 3월 1일

Not impressed with the teaching style.

Seems that lectures were being read and not taught.

교육 기관: Γεώργιος Κ

2018년 7월 4일

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.

교육 기관: Manoj K

2016년 2월 22일

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.

교육 기관: Павел Б

2016년 7월 25일

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

교육 기관: Ruben D S P

2018년 6월 29일

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

교육 기관: Bruno G C

2016년 10월 5일

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

교육 기관: Adrielle S

2018년 2월 6일

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.

교육 기관: Kostas P

2020년 5월 7일

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

교육 기관: Edward M

2016년 6월 25일

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

교육 기관: Dmitry B

2018년 1월 25일

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

교육 기관: Deleted A

2016년 6월 28일

Option of learning both SAS and Python is great!

교육 기관: Edita G

2020년 11월 30일

Great course about machine learning methods

교육 기관: Genara P

2017년 4월 6일

Excellet! I highly recommend!

교육 기관: Jinbo C

2017년 1월 7일

easy to capture the concept

교육 기관: Deleted A

2016년 9월 7일

short vedios and good ma

교육 기관: thoai n

2019년 12월 19일

This is good course

교육 기관: Karthik z

2017년 11월 9일

Well structured .

교육 기관: Yaman S

2016년 2월 28일

Excellent course

교육 기관: Santhosh K J

2019년 2월 25일


교육 기관: SHREYA S

2022년 6월 6일

Great Learning


2020년 7월 10일

Good to learn

교육 기관: Смирнов В Г

2018년 2월 26일

Great course!