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Вернуться к Практическое компьютерное обучение

Отзывы учащихся о курсе Практическое компьютерное обучение от партнера Университет Джонса Хопкинса

4.5
звезд
Оценки: 3,170
Рецензии: 607

О курсе

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation....

Лучшие рецензии

MR
13 авг. 2020 г.

recommended for all the 21st centuary students who might be intrested to play with data in future or some kind of work related to make predictions systemically must have good knowledge of this course

AD
28 февр. 2017 г.

Issues of every stage of the construction of learning machine model, as well as issues with several different machine learning methods are well and in fine yet very understandable detail explained.

Фильтр по:

526–550 из 598 отзывов о курсе Практическое компьютерное обучение

автор: Léa F

9 янв. 2018 г.

Rather good overview. The contents could dig deeper into each subject, and it would improve the course a lot if some exercises in Swirl were added.

автор: Miguel J d S P

19 мая 2017 г.

I didn't enjoy the supporting materials and the quizzes weren't very interesting. The final project was fine.

The subject is super interesting.

автор: Max M

12 дек. 2017 г.

Should have gone into more depth and included swirl lessons, like previous courses. The quizzes were very challenging though, so that helped.

автор: Kyle H

9 мая 2018 г.

A brisk introduction to some of the basics of Machine Learning. Will leave with an understanding of a few ways to use the caret package.

автор: Manuel E

8 авг. 2019 г.

Good course, but either explanations are too fast paced for the level of difficulty, or my neurons have began to decay with age.

автор: Noelia O F

19 июля 2016 г.

Good course for learning the basics of the caret package. However, it is not a good course for learning machine learning.

автор: Joseph I

1 февр. 2020 г.

Material was very interesting but was covered at a very high level and a lot of additional learning was required.

автор: José A G R

5 февр. 2017 г.

Superfluous but the existence of the package "caret" covers the gap of other libraries like "skilearn" of python

автор: BAUYRJAN J

1 мар. 2017 г.

Instructor rushes the course and does not explain much in the same level of details as respective quiz requires

автор: Hongzhi Z

2 янв. 2018 г.

All the formulas and code in slides are too abstract. If can be more charts to interpret that will be better.

автор: Henrique C A

13 окт. 2016 г.

Exercises could be more complete, and some are outdated for latest R, giving slightly different results.

автор: Alex F

29 дек. 2018 г.

A fine introduction, but there are much more engaging and better quality courses out there...

автор: Yingnan X

11 февр. 2016 г.

If you have taken Andrew Ng's machine learning class, it's not necessary to take this one.

автор: yohan A H

6 сент. 2019 г.

I think it was a very fast course and I feel more real examples would have been useful,

автор: fabio a a l l

14 нояб. 2017 г.

Poor supporting material in a course that tries to cover a lot in a very limited time.

автор: Rafael S

24 июля 2018 г.

this course seemed too rushed for me, too little content for such a extense subject

автор: Raj V J

24 янв. 2016 г.

more needs to be taught in class. what is taught is not sufficient for quizzes.

автор: Surjya P

2 июля 2017 г.

Overally course is good. But weekly programming assignments will be great.

автор: 王也

17 дек. 2016 г.

Too different for beginners but not deep enough for ones already know R.

автор: James F

10 сент. 2016 г.

Quizzes are useful exercises but need to do a lot of self studying.

автор: Philip A

26 февр. 2017 г.

mentorship was great, but the video lectures were almost useless.

автор: Christoph G

4 дек. 2016 г.

The topic is too big, for one course from my point of view.

автор: Ariel S G

27 июня 2017 г.

In my opinion, this course needs a few extra exercises.

автор: Jorge L

13 окт. 2016 г.

Fair but assignments are not very well explained

автор: Bahaa A

20 окт. 2016 г.

Good enough to open up mind of researcher