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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: 3,119
Рецензии: 591

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:

426–450 из 583 отзывов о курсе Практическое компьютерное обучение

автор: danxu

13 мар. 2017 г.

very good, but if it has swirl practice like th other courses it would be perfect.

автор: Christian W

31 янв. 2017 г.

First 3 weeks are manageable and the final project is great! I had a lot of fun :)

автор: Yew C C

4 февр. 2016 г.

Wish to have more systematic structure, detail information and hands-on exercises.

автор: vivek s

7 июня 2016 г.

introduces lot of machine learning techniques which are used by practitioners !

автор: Ramiro A

31 авг. 2016 г.

Nice course, Gives a god insight on what can me done with R and Predictions

автор: Daniel U

17 февр. 2016 г.

Fast paced and little focused on the algorithms but quite useful overall.

автор: Matthew L

6 янв. 2016 г.

Really good overview of machine learning techniques and model evaluation.

автор: Bhawani P

6 янв. 2017 г.

briefly summarised the machine learning algorithms. Good place to start!

автор: S M H R

10 февр. 2016 г.

A good course where you can learn how ML algorithms work practically.

автор: Saurabh K

9 мар. 2017 г.

Very useful course to develop level knowledge in machine learning.

автор: Johnny C

23 окт. 2018 г.

It was in general nice course. However, quizzes need improvement.

автор: Karthik R

7 авг. 2017 г.

Bit tough, but I will have to say, good introductory course.

автор: Coral P

18 авг. 2017 г.

The project is good in letting us practise what we learnt

автор: Trung N T

19 апр. 2018 г.

Thank you! My teacher. The course very good. Many thanks

автор: Shobhit K T

18 дек. 2017 г.

Great course with practical insights on machine learning

автор: Minki J

28 дек. 2017 г.

good to know many concepts of machine learning model.

автор: Shikhar K D

1 окт. 2020 г.

A very helpful course in this specialization series.

автор: Diego T B

7 нояб. 2018 г.

Very useful. The models were very easy to understand

автор: Grigory S

28 авг. 2018 г.

A bit short on practical aspects of different models

автор: Alfredo M

22 авг. 2016 г.

Excelente curso. Ótimo conhecimento dos instrutores.

автор: Carlos R

27 мая 2018 г.

Great Course! I have learned a lot of new things.

автор: Steve d P

20 мар. 2016 г.

Nice, other courses will go more in depth though.

автор: Stephan H

12 авг. 2017 г.

Very challenging course. I learned a lot. Tanks.

автор: YUCHEN Z

1 мая 2020 г.

not so pratical based on the current situation

автор: Manuel C

26 дек. 2017 г.

I feel I could have master the subjects better