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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: 3,169
Рецензии: 607

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 598 отзывов о курсе Практическое компьютерное обучение

автор: Yusuf E

17 окт. 2018 г.

It would have been nice if there was an introduction to deep learning. Also, linear methods are discussed at length again which is not really necessary. Otherwise, great course to get you started on machine learning applications in R.

автор: Athanasios S

9 авг. 2018 г.

Great class! I wish you would do a little more explanation about what methods are best for which scenarios. If you did in fact explain that and it went over my head or I missed it, I apologize. Great class that I learned a lot from.

автор: Dave H

23 февр. 2019 г.

This was one of my favorite courses in the specialization as it was so easy to understand and follow. I think the basis I was given has really made me want to delve deeper into the topic and apply it to my career. Thank you!!!

автор: Pei-Pei L

26 июля 2017 г.

This course covers a lot of information in a short time, but you'll feel very proud of yourself when you finish it! It made me feel much more comfortable with writing machine learning programs, and am ready for the next topic!

автор: Kristin A

9 янв. 2018 г.

Good intro to a topic that has a lot of power and a rich body of knowledge behind it. You can only scratch the surface in a four-week course, but I have been exposed to quite a range of tools in Practical Machine Learning.

автор: Samuel H

17 февр. 2016 г.

This was a very good introduction to machine learning and how to use machine learning packages in R. It would have been better if the class had been longer than four weeks, but I learned a lot for the length of the course.

автор: Mohammad A

17 янв. 2019 г.

Wonderful course and instructor, it was the best in the specialization courses so far.

One note is that for most of the methods the explanation was too much precise and short and needed to reinforce it by extra material

автор: manny d

9 сент. 2017 г.

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: 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: 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: German R M S

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.