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Вернуться к Практическое компьютерное обучение

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

4.5
Оценки: 2,667
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.

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476–491 из 491 отзывов о курсе Практическое компьютерное обучение

автор: Mehrshad E

Mar 28, 2018

This course really lack something like SWIRL. The lectures only provide a summary, which is not helpful for someone new to the machine learning. Also, the instructure tries to cover pretty much everything but not in depth; instead, I think fewer topics should be covered in depth.

автор: max

Jan 18, 2017

not what I expected for a machine learning course

автор: Y. B

Feb 06, 2016

incomplete and not clear. extremely disappointed.

автор: Felipe M S J

Dec 02, 2016

No es un curso en el que se aprenda demasiado.

Parece demasiado avanzado en el uso de "caret" y en vez de enseñar, parece ser que todo debe ser aprendido con anterioridad.

Todo el material adicional que se necesita en el curso, es en general contenido externo.

автор: Haolei F

Mar 13, 2016

Need to get more in-depth

автор: Marshall M

Sep 23, 2017

A lot of the concepts in the course are grazed over very briefly and don't go into that much depth. In addition, some of the concepts are taught as concepts, they are taught through examples which tends to contextualize the material. Good content but could be put together in a more in depth manner.

автор: Michael R

Oct 03, 2019

It's a mediocre intro to some machine learning tools. I think the course materials could be drastically improved.

автор: Stephen E

Jun 27, 2016

To be honest I don't think this is worth the money.

автор: Gianluca M

Oct 20, 2016

Gosh I hated hated hated this course. Nothing to learn here. You will just be given lots of names with no explanation whatsoever.

I often felt really angry at the teacher because of the way he would introduce entire prediction models without explaining anything about them. Also, I really didn't like the fact that the course is centered on caret, a "shortcut" package to do stuff fast. Before doing things fast I need to know what I am doing! Finally, the quizzes and assignments are completely disconnected from the courses.

The worst course I have ever taken on coursera.

автор: Jo S

Feb 04, 2016

Poor compared with some of the others on this specialisation. The lectures are too fast and high level, with no allowance given for people who are unfamiliar with this area and attempting to learn it.

автор: Robert O

Apr 06, 2016

Very little depth. I don't recommend this if you don't already have background in statistics or R. I really didn't learn anything. I mostly just gamed the quizzes and projects.

автор: Stephane T

Jan 31, 2016

Too much surface, not enough depth.

автор: Thomas H

Feb 08, 2016

Project description versus requirements were terrible, not sure if the new Coursera format played a role in the issues or not. Quite a few of the homework items require guessing as the answers don't align to the results of the latest tools they have you use. If the first class or three in the series was like this I wouldn't have taken the courses.

автор: Danielle S

Mar 22, 2016

Material is very high level. No ppt's are given, so all links presented in the video's cannot be viewed.

Quizzes are based upon old packages, so incorrect answers are provided.

No replies at discussion board from TA"s or instructors.

автор: Etienne B

Mar 01, 2016

Cannot take the exam, I have to pay... wtf... I will probably pay at the end, but I want to take the class first. Without certificate I cannot prove I took the course.

автор: yi s

Jul 19, 2016

too general no depth, not recommended for science or engineering degree holders