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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: 3,055
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.

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51–75 из 570 отзывов о курсе Практическое компьютерное обучение

автор: ARVIND K S

23 мая 2020 г.

It 's a great machine learning course for beginners as well as students with experience. The quizzes and peer assignments are invaluable and if done with a purpose can augment knowledge of the subject immensely.

автор: Joseph

13 дек. 2016 г.

Awesome course. Jeff Leek does a truly amazing job at explaining very complicated concepts thoroughly and quickly. I'm surprised we went through as much material as we did. Out of the 9, this is one my favorites.

автор: Adam R

11 нояб. 2018 г.

Best course in the data science series. It is practical, so if you are looking for something theoretical this will not be the course for you. Also good introduction the methods for model testing and validation.

автор: Massimo M

21 апр. 2018 г.

Very interesting course, materials are explained in an engaging manner. I would have loved to have a few more exercises to practice, but overall a good course to understand the most important concepts of ML.

автор: Ben H

7 окт. 2019 г.

Really nice introduction to machine learning in R. You wouldn't want to pack more than this in 4 weeks. Would be interested to see if this course adopts the recipes / parsnip / tidymodels in the future.

автор: Anuj P

21 февр. 2019 г.

This is the most interesting of all the courses in this specialization. Sometimes the content covered can be overwhelming. But the end result in the form of project assignment is worth all the efforts.

автор: Jerome C

17 янв. 2017 г.

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: Vivek G

9 нояб. 2020 г.

Great introduction to ML.

Demands focus and hard work.

Forces one to review earlier courses - Statistical Inference, regression models, EDA.

Leaves lots of appetite for additional knowledge and skills.

автор: Muhammad R

14 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

автор: Angel D

1 мар. 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.

автор: Dale H

17 июня 2018 г.

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.

автор: Araks S

30 авг. 2017 г.

Highly recommend this course. It makes you read a lot, do lot's of practical exercises. The final project is a must do. After finishing this course you can start playing with kaggle data sets.

автор: Rafael M

13 нояб. 2018 г.

Este es un muy buen curso, aprendes lo básico para poder entrar en el mundo del machine learning y te da la oportunidad de desarrollar modelos realmente útiles.

Recomendado, definitivamente.

автор: Jared P

25 июня 2017 г.

Awesome course. Would recommend it, but only to those who have a bit of stats and R background. This definitely helped me get a solid enough understanding of using R for machine learning.

автор: Simeon E

2 авг. 2017 г.

Great Course. No so easy, as I expected, but, definitely, it worth all the time I've spent on it. Be careful: it requires a lot of self-studying and don't forget to read the Course Forum.

автор: Harris P

16 янв. 2017 г.

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: Nikhil K

19 февр. 2016 г.

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: Caner A I

12 апр. 2017 г.

Jeff Leek is a great professor .The delivery of the course material is very clear and covers a lot of predictive methods by using mainly R's caret package. Recommended for sure.

автор: João F

14 февр. 2019 г.

Very good course. Clear explanations and examples give a good overview of the foundations of Machine Learning. After this course the student can build Machine Learning models.

автор: Lopamudra S

3 февр. 2018 г.

The practical machine learning course is a booster for the data science aspirant.The concept taught by the Prof Jeff Leek is easily understandable. Thank you so much Sir.

автор: Keidzh S

15 июля 2018 г.

Practical Machine learning helped me to achieve my personal goals. Algorithm of prediction became clear, that gives the understanding of main point of the data science.

автор: Greg A

22 февр. 2018 г.

A great course that really helps demystify what machine learning is and how anyone can use it to build prediction models and start to answer tough questions using data.

автор: Florian

9 июля 2016 г.

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: Supharerk T

7 мар. 2016 г.

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: Saul L

8 февр. 2016 г.

This is by far the most enlightening class in the whole specialization. I really got a good handle about how to build a predictive model and apply it to real datasets.