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Вернуться к Практическое компьютерное обучение

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

4.5
Оценки: 2,671
Рецензии: 500

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

JC

Jan 17, 2017

excellent course. Be prepared to learn a lot if you work hard and don't give up if you think it is hard, just continue thinking, and interact with other students and tutors + Google and Stackoverflow!

AD

Mar 01, 2017

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:

76–100 из 492 отзывов о курсе Практическое компьютерное обучение

автор: Avirup N

Mar 07, 2016

Very informative

автор: Fernando S e S

Jul 24, 2016

It's hard as hell, and very good.

автор: KOALA V

Sep 25, 2017

Very interesting course

автор: Rui R

Feb 06, 2017

One of the best courses in the Data Science Specialization,

автор: Emanuele M

Nov 15, 2016

It very well done, good pace, and gives you real and concrete elements and examples to build a fully functional machine learning algorithm! i recommend this course

автор: Piotr K

Oct 23, 2016

Nice introduction to machine learning in R. It is rather basic level, so it not for people that already know some basics related to regression and classification.

автор: Jeremy O

Mar 10, 2017

excellent!

автор: Light0617

Sep 04, 2016

great!!! In this lecture, I learn how to write R code to analyze data with Machine learning methods.

автор: Divvya.T

Oct 29, 2017

Good course to take !!

автор: Shivanand R K

Jun 21, 2016

Great and Excellent thoughts and course material.

автор: Do H L

Mar 10, 2016

Useful course that is very practical in teaching tools in R that enable Machine learning. This course is, however, not suitable for people who want to learn theoretical machine learning. For that, learners will find Machine Learning by Andrew Ng a better alternative. However, if you're interested in machine learning packages in R and how to implement them, this course achieves that purpose for you.

автор: aditya n p

May 12, 2016

Awesome Course !!

автор: Angel D

Mar 01, 2017

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.

автор: Forest W

Jan 09, 2018

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

автор: Nirav D

Apr 02, 2016

This is a very useful course in Machine Learning that teaches us how to use the R based packages such as CARET for applying machine learning techniques. The course project helps understand how these techniques are applied in real world applications and develop useful insights.

автор: Supharerk T

Mar 07, 2016

I want to learn ML in R so I go straight to this course without taking any other course in this specialization, and it doesn't disappoint me. Thanks for a great course!

автор: Florian

Jul 09, 2016

Great primer for machine learning with ample additional resources for those who are interested. I feel this course gave me a solid basis to delve deeper into the topic.

автор: Sebastian F

Jan 24, 2016

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

автор: Rudolph A M

Oct 21, 2016

Wonderful!

автор: PRAKASH J M

Dec 25, 2017

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

автор: David S

Feb 07, 2016

The course gives a clear explanation of why machine learning, with a goal of prediction, is different from regression. The use of the caret package in R is emphasized. Caret provides a uniform interface to many different machine learning algorithms, leaving no excuse for practitioners not to test a variety of approaches to confirm the robustness of their conclusions.

автор: Robert K

Sep 26, 2017

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

автор: Arunkumar M R

Sep 30, 2017

Awesome course. Super effective quizzes.

автор: Jay S

Aug 27, 2016

Excellent introductory course to Machine Learning. Very informative materials. Prof. Leek is a great teacher.

автор: Jorge M A A

Apr 13, 2016

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