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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 26~50

교육 기관: Thomas C K

2016년 10월 11일

Great Class!

교육 기관: Amrutha K A

2020년 9월 27일


교육 기관: JADHAV R B

2020년 9월 16일

very good

교육 기관: Jyoti P K

2020년 9월 9일


교육 기관: Тефикова А Р

2018년 3월 20일

все супер

교육 기관: Tejas G

2020년 8월 31일

nice one

교육 기관: Artem A

2016년 4월 14일


교육 기관: Steven L

2017년 8월 30일


교육 기관: Sharath C S

2020년 9월 25일


교육 기관: keerthana G

2020년 9월 21일


교육 기관: Mansi S G

2020년 8월 24일


교육 기관: Mathilde v E

2016년 7월 21일


교육 기관: Shreyans J

2019년 6월 27일

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.

교육 기관: Michael B

2017년 1월 3일

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.

교육 기관: Christine R

2017년 8월 15일

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

교육 기관: Manikanta K

2020년 4월 27일

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.

교육 기관: Mengyue S

2016년 3월 21일

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

교육 기관: ADITYA Y P

2018년 1월 6일

More Implementation oriented and less math

also contains distracting background videos when explaining important concepts

교육 기관: Oriana A

2017년 3월 21일

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

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

교육 기관: Leonardo A

2016년 10월 31일

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

교육 기관: Ivan C

2016년 3월 3일

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

교육 기관: Drew M

2018년 10월 13일

Learned some really useful ML models.

교육 기관: Kailas R

2020년 8월 18일

Good course for beginners

교육 기관: krushna l

2020년 9월 14일

it is very useful to me

교육 기관: Lee X

2016년 3월 21일

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.