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Вернуться к Практическое компьютерное обучение

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

4.5
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Оценки: 2,768
Рецензии: 519

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

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.

DH

Jun 18, 2018

Excellent introduction to basic ML techniques. A lot of material covered in a short period of time! I will definitely seek more advanced training out of the inspiration provided by this class.

Фильтр по:

501–510 из 510 отзывов о курсе Практическое компьютерное обучение

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: 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: 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: Eduardo S B

Jan 26, 2020

They explain nothing on the fundamentals of the machine-learning methods, nor how to know which method apply to a given problem.

автор: Abhilash R N

Dec 04, 2019

This course is NOT for the beginner. Take time to finish all the beginner and foundation courses and then take time to learn R

автор: yi s

Jul 19, 2016

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

автор: Stephen E

Jun 27, 2016

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

автор: Stephane T

Jan 31, 2016

Too much surface, not enough depth.