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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: 3,168
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:

151–175 из 598 отзывов о курсе Практическое компьютерное обучение

автор: Enrique A

18 окт. 2020 г.

Mil Gracias Maestro Roger y demas docentes, Mil gracias U. John Hopkins, Mil Gracias Coursera.

автор: Gustavo C G

7 авг. 2019 г.

Excellent introduction to machine learning. Great examples and detailed explanations, as usual

автор: Theodoros M

10 июля 2018 г.

Practical ML is a great course, that provides training in the practical aspects of the topic.

автор: Wesley E

15 февр. 2016 г.

Great introduction with a broad set of tools and plenty of resources for more in depth study.

автор: André C L

13 дек. 2018 г.

very good practical experience using machine learning models, especially regarding PCA usage

автор: Raunak S

19 нояб. 2018 г.

a very good course for those wanting to learn Machine Learning to implement in Data Science.

автор: Tristan F

25 дек. 2019 г.

Lectures were very clear and helpful! Professor Leek was great at breaking down the topics.

автор: Oleksandr K

11 июля 2018 г.

Great course! However, it would be good to learn about artificial neural networks as well.

автор: Jean N

24 авг. 2017 г.

Very nice Course. I am applying it right away for Predictions in the Telecoms environment.

автор: Tomer E

6 авг. 2020 г.

Great course!

Covers basics of machine learning algorithms and how to implement them in R.

автор: Rizwan M

13 окт. 2019 г.

great course. could have explained more techniques in caret package with coding examples

автор: Connor B

24 сент. 2019 г.

Really good exposure to machine learning and builds on the previous course in regression

автор: Alfonso R R

13 нояб. 2018 г.

Hands on course. Loved it. It goes a little bit fast, however, the content is ambitious.

автор: Brian G

17 авг. 2017 г.

Great course. Mechanics of the final assignment are more difficult than the work itself.

автор: Paresh P

8 дек. 2020 г.

Explained practical machine learning well, concepts like model stacking really helped!

автор: Sean D

10 июня 2020 г.

Really liked Dr. Leek's talks, and the subject matter was interesting and kind of fun.

автор: Konstantin

2 мар. 2020 г.

Excellent course. Lots of exorbitantly useful knowledge. I`ve been lucky to start it.

автор: Donson Y

4 сент. 2017 г.

This is a fantasy course to know that how to build your first machine learning model.

автор: Jorge M A A

13 апр. 2016 г.

I enjoyed a lot this module, I'll use at my daily work some of the features I learned

автор: Premkumar S

16 мар. 2019 г.

Great course and farily challenging exercises! Thank You for putting this together!!

автор: Sai S S

17 июля 2017 г.

Great course. Ways to curb plagiarism & cheating needs to be revisited by your team.

автор: Thet P S A

21 авг. 2020 г.

It supports a lot in my thesis. Thank you, lecturers, at John Hopkins University.

автор: Mary

19 авг. 2019 г.

Very informational with good variety of code to take back and apply to projects.

автор: Nikhilesh J

2 мар. 2018 г.

Provides a quick and dirty look at Machine Learning. An easy way to get started.

автор: Jeffrey M H

10 июня 2019 г.

So far, one of the most fulfilling courses in the Data Science specialization!