Chevron Left
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:

201–225 из 491 отзывов о курсе Практическое компьютерное обучение

автор: Chris N

Jun 07, 2017

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

автор: hyunwoo j

Apr 10, 2016

johns hopkins' courses very helped me

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: 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: Ivan Y

Mar 06, 2018

great intro to machine learning!

автор: sampath

Oct 13, 2017

Tough but very good course

автор: Raju G

Nov 26, 2017

Extremely useful.

автор: Evgeniy Z

Apr 12, 2016

Nice course.

автор: Madhuri

Mar 23, 2016

I like the organisation of the course. The first video is so informative yet so simple. Great resources have been listed in it and so subtly. Also I saw the organization of folders and lecture notes and everything in Github repo for this course. It s awesome. I keep stuff like that.. well numbered and everything. I really appreciate it as it makes life of a student lot easier. Thanks.

автор: SATHYANARAYANAN S

Sep 11, 2017

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

автор: Marcus S

Feb 11, 2016

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

автор: Massimiliano F

Feb 17, 2017

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

автор: benjamin s

Jul 09, 2018

Probably the most enjoyable course of the specialisation, more maths would improve the quality of the content

автор: Jerome C

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!

автор: Harris P

Jan 16, 2017

It was like opening up a door to a whole new world. I have discovered new tools that I will thoroughly enjoy to use for the exploration of data and for predictions. Thanks Team Coursera !

автор: Gary R S

Dec 31, 2017

Excellent intro to machine learning with interesting projects.

автор: Billy J

Apr 13, 2016

Excellent introduction to machine learning. I feel that I have a good basic foundation to start building upon.

автор: manny d

Sep 10, 2017

Best course i have ever taken on Machine Learning! Excellent presentation and excellent reference sources. Machine Learning is not that hard as I thought it would be..please make more practical courses like this one.

автор: Nikhil K

Feb 19, 2016

Some of the terms used here vary from the terms used in the industry. For example recall, precision etc. Overall this is a very good course with provides basics of machine learning.

автор: andy p

Aug 10, 2016

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: Robert H

Apr 14, 2017

Really hands-on compact introduction!