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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: 3,054
Рецензии: 579

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:

126–150 из 570 отзывов о курсе Практическое компьютерное обучение

автор: HARSH L

11 июля 2016 г.

Awesome course giving a practical experience of a Data Scientist.

Perfect place to get your hands dirty! :)

автор: Andrew

23 июля 2019 г.

Great intro to machine learning. Covers the basics to allow you to being using ML concepts on your own.

автор: Julio G C

10 февр. 2018 г.

It is exactly what you need to begin in datascience.

Very good client's service if you've some problem.

автор: Charbel L

7 сент. 2019 г.

Excellent course. Shows how simple it is to start running models with machine learning...! Well done

автор: Light0617

4 сент. 2016 г.

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

автор: Channaveer P

20 апр. 2020 г.

Excellent course. Enables student to understand multi variable regression and comparing accuracies.

автор: Policarpio S

28 мар. 2016 г.

I really enjoyed this course. The material was concise and allows me to get up and running with ML.

автор: Gustavo E L

14 мар. 2016 г.

With this course, you can develop an important skill for the final steps of a data science project.

автор: Yadder A

31 окт. 2019 г.

It's the best course I've taken. It has all the basics about machine learning algorithms and more.

автор: Yap Y A

10 мар. 2019 г.

Instructor was clear in his explanation. Would prefer to have more hands on exercise for practice

автор: Weiqun T

23 сент. 2019 г.

This is a very good basic course for machine learning. I got the basic ideas and skills for it.

автор: Сетдеков К Р

3 февр. 2020 г.

Great course! Very useful to train using advanced classification models and ensemble learning.

автор: Krishna P

20 июня 2016 г.

Very good content for beginner, lot of learning in machine learning special caret package in R.

автор: Enrique A M

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