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Отзывы учащихся о курсе Convolutional Neural Networks in TensorFlow от партнера

Оценки: 6,742
Рецензии: 1,049

О курсе

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In Course 2 of the TensorFlow Specialization, you will learn advanced techniques to improve the computer vision model you built in Course 1. You will explore how to work with real-world images in different shapes and sizes, visualize the journey of an image through convolutions to understand how a computer “sees” information, plot loss and accuracy, and explore strategies to prevent overfitting, including augmentation and dropout. Finally, Course 2 will introduce you to transfer learning and how learned features can be extracted from models. The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization....

Лучшие рецензии

12 нояб. 2020 г.

A really good course that builds up the knowledge over the concepts covered in Course 1. All the ideas are applicable in real world scenario and this is what makes the course that much more valuable!

14 мар. 2020 г.

Nice experience taking this course. Precise and to the point introduction of topics and a really nice head start into practical aspects of Computer Vision and using the amazing tensorflow framework..

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751–775 из 1,041 отзывов о курсе Convolutional Neural Networks in TensorFlow

автор: Rakesh G

16 янв. 2020 г.

I think this was a good course but the standard of exercises and quizzes was too easy. More conceptual questions especially in quizzes would help in understanding the topic better

автор: ashish s

22 апр. 2020 г.

Overall good. Could have gone in bit more depth on how various hyper parameter tuning and regularization methods impact the model training. Provide some best practices tips .

автор: Gerardo S

26 сент. 2019 г.

the last exercise needed a big upload, made it imposible (for me) to do. This was a problem not related to the subject, should use data downloadable directly from internet.

автор: Sokratis A

30 мар. 2021 г.

Most of the Programming Assignments are a copy-paste routine from colab notebooks provided

the last one was pretty challenging though ^_^

(Im experienced in Programming)

автор: Eric L

10 дек. 2020 г.

This course only requires few hours of work and I would like to see more depth. The parts on image augmentation and transfer learning were pretty interesting though!

автор: Luciano C

31 дек. 2020 г.

Curso muito legal, a única coisa que ficou um pouco abaixo do esperado foi o último exercício da quarta semana, não foi construído com o cuidado visto nos outros.

автор: Vishwanadha K V

22 июня 2020 г.

The assignments are not challenging enough. The concepts are really well explained and for someone with no background in this area, this is a great learning asset

автор: Dimitry I

10 авг. 2019 г.

Very good course that teaches you basics of convolutions, augmentation, transfer learning. Thank you to Mr. Moroney and the Coursera team for making it available.

автор: vaibhav t

26 июня 2020 г.

The course was good. The only problem was the last assignment where some of the functions went missing. It was difficult for a beginner to catch such glitch

автор: chaitanya m

15 апр. 2020 г.

The best course to do. Especially after the specialization course from Andrew. It is really helpful to code all the concepts you learned from Andrew course.

автор: Ujjwal G

16 нояб. 2019 г.

I think most much of the course conent was same as the first course, this course could have been a little more advanced. But overall a great place to start.

автор: Moritz R

24 янв. 2021 г.

Very nice the step from the first course was really nice. The achievements were harder to reach an all over the cose was less buggy than the first one. :)

автор: Estefania T

2 июня 2020 г.

The contents are a bit light from my point of view. I get it is to be accessible for more people but math and explanations are in some cases important

автор: Toqa A M E

4 апр. 2021 г.

it was great course but I need some more details and the speaking was a little difficult as some of words are slang and the translation was so bad

автор: Subham S

23 дек. 2019 г.

The course content was quite good and overall understandable but the exercises and quizzes were quite easy, they could have been more challenging

автор: Pray S

23 апр. 2020 г.

The hand sign assignment need more explanation about using flow object from ImageDataGenerator since I just know only flow_from_directory object

автор: DING T K

14 февр. 2021 г.

Learn a lot for CNN in this course, but require advance knowledge in Python & Numpy to understand the code as it was not explain in the course.

автор: 屈佑平

28 нояб. 2020 г.

Exercise_4_Multi_class_classifier_Question-FINAL has problem if you entirely follow the tips, you can find the correct code in the forums.

автор: Gianluca T

17 сент. 2020 г.

Very nice and interesting videos, cool concepts, amazing datasets. Exercises lack sometimes clear objectives, or provide unclear feedbacks

автор: Rodolfo V d A

10 июля 2020 г.

I guess one thing was not studied, the method .flow() which get the images generated by keras with the dataset labeled for the final test.

автор: Shubham S

6 дек. 2020 г.

Lectures videos are amazing but the only problem in programming assignments. Programming assignments should have been properly designed..

автор: Abhiram

12 мар. 2020 г.

More detail videos or links,examples for important techniques like dropouts and for like multi class classification which may be optional

автор: Madhu

13 дек. 2020 г.

Content was great. It was insightful. However I felt, in few assignments, the instructions were misleading and took some to figure out.

автор: Ghifari A F

14 мая 2020 г.

The course is very useful for practical purposes. But this course didn't cover some advanced topics such as object detection and GAN.

автор: Nikos R

19 окт. 2020 г.

Very good course to get you started on convolutional neural networks. Week two had a small problem with the programming assignment.