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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: 3,155
Рецензии: 604

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:

176–200 из 595 отзывов о курсе Практическое компьютерное обучение

автор: Forest W

9 янв. 2018 г.

Much Better than the previous courses ( Regression and Statistical Inference)

автор: Chris H

23 мая 2016 г.

Great course. I really enjoyed working on the prediction project at the end.

автор: Marcus S

11 февр. 2016 г.

Great introduction to the subject with good classification examples using R.

автор: Gayathri N

21 сент. 2020 г.

Wonderful foundational course to understand the basics of machine learning.

автор: Sarah S

31 мая 2017 г.

I enjoyed detailed information and was very straight forward to understand.

автор: SATHYANARAYANAN S

10 сент. 2017 г.

Very good for anyone wanting to get into the field of Data Science using R

автор: Sandro G

13 окт. 2017 г.

I have learnt a lot of thing and very happy to have followed this course

автор: Camilo Y

14 мар. 2017 г.

This course is a good introduction to machine learning algorithms with R

автор: Massimiliano F

17 февр. 2017 г.

In my opinion, the best course of the entire Data Science Specialization

автор: Diana S

11 февр. 2016 г.

Thank you son much!!!!

I really like the course.

It help me in my job =)

автор: Mehrdad P

20 нояб. 2019 г.

Overall was a great course for an overview of the techniques available.

автор: Filippo C

3 мая 2020 г.

It was very interesting. It sparked the interest to deepen this topic!

автор: Robert J C

27 окт. 2019 г.

It gets harder but fun...R, as well Python and Matlab, can do AI well.

автор: Bruno R S

7 мар. 2019 г.

a quick introduction to the basic algorithms for machine learning in R

автор: Mehdi Z

25 мар. 2016 г.

Hands-on training, practical introduction to machine learning using R!

автор: Ray W

21 мар. 2016 г.

Principle and practices. Good coverage on topics to get you started!

автор: Bojan B

14 окт. 2018 г.

Great course with great materials. Easy to understand and to learn.

автор: Sebastian F

24 янв. 2016 г.

Great course. Really educational and informative. Well taught too!

автор: Roberto D

20 июня 2017 г.

Methods to be applied in preparation for creating a data product.

автор: Reza M

9 июля 2020 г.

Excellent engaging course. At times difficult but very enjoyable

автор: Alejandro B G

9 февр. 2016 г.

A great Course, my favorite into the Data Science Specialization

автор: Gary R S

31 дек. 2017 г.

Excellent intro to machine learning with interesting projects.

автор: PRAKASH J M

25 дек. 2017 г.

Pushed me to learn and experiment and make mistakes. Thank you

автор: Aleksey K

9 февр. 2016 г.

Made many things clear. Perhaps, the best class in the series.

автор: Anna O

4 нояб. 2020 г.

a simple way of real practice of machine learning algorithms.