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Отзывы учащихся о курсе Image Classification with CNNs using Keras от партнера Coursera Project Network

4.4
звезд
Оценки: 532
Рецензии: 80

О курсе

In this 1-hour long project-based course, you will learn how to create a Convolutional Neural Network (CNN) in Keras with a TensorFlow backend, and you will learn to train CNNs to solve Image Classification problems. In this project, we will create and train a CNN model on a subset of the popular CIFAR-10 dataset. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your Internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with (e.g. Python, Jupyter, and Tensorflow) pre-installed. Prerequisites: In order to be successful in this project, you should be familiar with python and convolutional neural networks. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

Лучшие рецензии

VN
10 авг. 2020 г.

This is a very good guided project.\n\nI thank Amit Yadav and Coursera for his teaching in Image Classification with CNNs using Keras.\n\nThank You

SB
2 июня 2020 г.

Really enjoyed learning from Amit Yadav. He promptly answers any query posted in the discussion forum. Looking forward to learning more from him.

Фильтр по:

51–75 из 80 отзывов о курсе Image Classification with CNNs using Keras

автор: Rifat R

6 июня 2020 г.

Nice

автор: Ankit G

11 мая 2020 г.

GOOD

автор: Patil B

2 мая 2020 г.

nice

автор: Rakesh k

24 мая 2020 г.

No

автор: Chintoo K

16 сент. 2020 г.

Good job by the instructor. But for a beginner to choose a particular dataset and performing image classification during preprocessing becomes a cumbersome task. CiFAR 10 dataset is already available in tf.keras's load_data module but using cv2 to read images and assigning label for any real world dataset would be more appreciable .

автор: Wittaya P

3 июня 2020 г.

I understand that it is quite hard to explain how to code these scripts since the first task, it is not suitable for the Python and CNN beginner at all. However, the color code (red and green) is not explained deeper in more details, so that the output photos with colored texts are different from they should be.

автор: Marcos R A

28 июня 2020 г.

For me the project was what I expected for a 1-hour project, but it would be great if it could be performed without the virtual machine, it's quite problematic and I couldn't type some symbols (= or []) with the common combinations of my keyboard. Besides this, I really enjoyed this mini project.

автор: Wan M A B M N

22 окт. 2020 г.

The tutorial was good but it would be great if theory is also being explain in details during the tutorials. This could help people to relate to the theory they learn and at the same time get to apply it during tutorials.

автор: PRAGYA A

19 мая 2020 г.

it was short n up to the mark, fully hands on and i came to know many new terms and their working. as it is a 1 hr assignment, this is just sufficient and satisfactory for beginners.

автор: Mazhar M

30 сент. 2020 г.

Rhyme interface is very bad and slow,

I would not pay for courses on rhyme if it were not sponsored by my college

Very good content though for a begginer

автор: Bhanu P M

20 июля 2020 г.

Perfect project for polishing you deep learning skills mainly CNN and getting introduced to using dataset available globally.

автор: Maddala N

5 июня 2020 г.

The project is good and the instructor explains the main areas of the code very well.

автор: Shashank J

6 июня 2020 г.

Course was good but rhyme interface was bad and needs an improvement

автор: Monica S A

29 мая 2020 г.

it is very useful for my career development. I like this very much

автор: Vedant A K

9 мая 2020 г.

Not in depth, but still good for understanding

автор: DEEPA G

19 апр. 2020 г.

Thank you...this course too helpful to me

автор: Om P

7 мая 2020 г.

Not in much details, still worth a try.

автор: Kuldeep S S

3 мая 2020 г.

Good Project for Biggener

автор: Md. M H

30 мая 2020 г.

so helpfull

автор: SUSHANTA K S

7 авг. 2020 г.

Good

автор: Pravendra S

29 июня 2020 г.

nice

автор: Krishan A

12 мая 2020 г.

EASY

автор: KAUSHIK R V

3 мая 2020 г.

e

автор: Pragati

4 июня 2020 г.

Please, explain the structure of the data used and also the libraries used before starting the actual project.

автор: Baliram C

12 июля 2020 г.

If you do not know the theory about CNN its nothing at all cause code is found everywhere.