Chevron Left
Вернуться к Практическое компьютерное обучение

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

Оценки: 3,159
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

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

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:

101–125 из 595 отзывов о курсе Практическое компьютерное обучение

автор: Chris N

7 июня 2017 г.

loved it - fascinating subject and more detail than you could possibly want from the course instructors. Friendly community in the forum too.

автор: Matthew W

1 мар. 2016 г.

High level and brief overview but found it informative introduction into machine learning with R. The final project is fun and interesting.

автор: Javier A D

27 мая 2018 г.

References were very usefull for doing deep analisys in the thems

Quices were challenge.I learn a lot solving them.

I mis the swirl sessions

автор: Mickey K

15 июля 2021 г.

Although I had no knowledge on the subject, the instructor presented it in such a clear way, that I understood it completely by few weeks.

автор: Swaraj M

5 мая 2020 г.

Thank you coursera for helping to get the fundamentals of machine learning, now I am confident enough to switch my career in data science.

автор: Laro N P

22 июля 2018 г.

Good course, I miss more practice exercise because theory is always welcome but when we are capable to understand is doing real practice.

автор: Sanjay J

6 окт. 2020 г.

Fantastic course, and loved the hand's on projects and assignments. Good course to practically get started in machine learning using 'R'

автор: Gustavo S

19 апр. 2020 г.

Very nice course, well-explained, sometimes a little bit fast if you dont have the luck of having previous knowledge.

100% recommendable

автор: Susan M

10 дек. 2020 г.

Excellent instruction followed up with projects to enable thorough understanding as well as ability to use the data science skillset.

автор: Nathan M

11 июня 2016 г.

Extremely useful class! Jeff also has many excellent suggestions for resources that will teach you even more about machine learning.

автор: Diandian Y

28 нояб. 2019 г.

a broad coverage of content and very intuitive explanation for different algorithm. Good start point to learn machine learning.

автор: Avizit C A

30 янв. 2019 г.

A very good course giving brief descriptions and applications of some of the used statistical and machine learning algorithms.

автор: Dan K H

27 мар. 2017 г.

Yet again an excellent course by Jeff, Roger and Brian. Thank you very much for a well layout course and some good excersizes.

автор: Peter D

7 окт. 2016 г.

One of my favorites in the series! What I have been waiting for building up the prerequisite knowledge. Enjoy the instructor!

автор: andy p

9 авг. 2016 г.

Great topic with a great instructor. Only wish the program was a little longer to spend some more time on some of the models.

автор: Prakhar P

6 июня 2018 г.

This course introduces to the machine learning package caret. A solid launch pad into the exciting world of data analytics.

автор: Moises E

16 янв. 2017 г.

Very good overview and straightforward explanations of the different methodologies of ML. Nice tips on how to do ML with R.

автор: Daniiar B

29 сент. 2018 г.

It lucks theory, but that's why it's called practical. Very hands on teaching method. Was a little bit hard to follow.

автор: manuel s g

27 апр. 2021 г.

I learn a lot on this one. Always complex when it is a long time since last maths studies and university eneded ;-)

автор: Sabitabrata M

10 июня 2018 г.

Good course. Good overview on Machine Learning. But to understand the concepts I had to consult external resources.

автор: Robert K

26 сент. 2017 г.

A great introduction to machine learning and it does a good job building on the material from the previous classes.

автор: Pam M

19 мая 2016 г.

Good material, presented in an organized fashion. I was able to apply what I learned immediately in a work setting.

автор: Rahimullah S

28 окт. 2018 г.

thank you, this class is very practical and informative. The projects are a little complicated but very practical.


18 дек. 2019 г.

A Great course that should be taken along other books, tutorials, and papers, in order to get the most out of it.

автор: Matt S

8 мая 2019 г.

Good introduction to machine learning. Provides pretty comprehensive coverage of major algorithms and approaches.