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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: 3,132
Рецензии: 595

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.

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576–586 из 586 отзывов о курсе Практическое компьютерное обучение

автор: Ricardo G C

17 июня 2020 г.

The professors are experts on the subject, but unfortunately they rush through content and some of the classes are outdated (i.e. they use packages and data that are not the newest version) and this generates confusion througout the course.

автор: Danielle S

22 мар. 2016 г.

Material is very high level. No ppt's are given, so all links presented in the video's cannot be viewed.

Quizzes are based upon old packages, so incorrect answers are provided.

No replies at discussion board from TA"s or instructors.

автор: Jo S

4 февр. 2016 г.

Poor compared with some of the others on this specialisation. The lectures are too fast and high level, with no allowance given for people who are unfamiliar with this area and attempting to learn it.

автор: Robert O

6 апр. 2016 г.

Very little depth. I don't recommend this if you don't already have background in statistics or R. I really didn't learn anything. I mostly just gamed the quizzes and projects.

автор: E B

1 мар. 2016 г.

Cannot take the exam, I have to pay... wtf... I will probably pay at the end, but I want to take the class first. Without certificate I cannot prove I took the course.

автор: Eduardo S B

26 янв. 2020 г.

They explain nothing on the fundamentals of the machine-learning methods, nor how to know which method apply to a given problem.

автор: Abhilash R N

4 дек. 2019 г.

This course is NOT for the beginner. Take time to finish all the beginner and foundation courses and then take time to learn R

автор: Emily S A

25 мая 2020 г.

In my opiion, this course needs to be improved a lot. There are almost nothing Practical Machine Learning.

автор: yi s

19 июля 2016 г.

too general no depth, not recommended for science or engineering degree holders

автор: Stephen E

27 июня 2016 г.

To be honest I don't think this is worth the money.

автор: Stephane T

31 янв. 2016 г.

Too much surface, not enough depth.