Chevron Left
Вернуться к Convolutional Neural Networks in TensorFlow

Отзывы учащихся о курсе Convolutional Neural Networks in TensorFlow от партнера

Оценки: 7,651

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


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..


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!

Фильтр по:

951–975 из 1,179 отзывов о курсе Convolutional Neural Networks in TensorFlow

автор: Taras B

23 мар. 2022 г.

It will be very nice to have more coding exercices.

автор: Haoran C

4 сент. 2019 г.

Please transfer the notebook from CoLab to Coursera.

автор: Robert G

11 дек. 2019 г.

I would like to see examples with videos, yolo, etc

автор: KHODJA

2 окт. 2019 г.

A more advanced course would be highly appreciated.

автор: Ruiwen W

22 июля 2020 г.

Assignment material not very aligned with lectures

автор: Gerardo S

16 сент. 2020 г.

I feel like this series of courses is too narrow

автор: Ahmet K

30 дек. 2019 г.

Nice course! All detailed and explained. Thanks!

автор: Jay T

1 сент. 2020 г.

A bit hard to understand the final assignment.

автор: Kailyn W

9 сент. 2019 г.

I need more coding practice, not just quizzes.

автор: Michel M

6 авг. 2019 г.

The final assignment was somewhat a steep step

автор: Zhi Z

6 июля 2019 г.

A good course for Keras but not for tensoflow.

автор: Aleksander W

14 февр. 2021 г.

better than course #1 of this specialisation

автор: Surya n T S

24 окт. 2021 г.

A very practical approach towards learning.

автор: Prabhat K G

29 мая 2020 г.

Last assignment needs much more explanation

автор: RAVI P

17 июня 2020 г.

Programming exercises are a bit confusing.

автор: Dr. S G

17 апр. 2020 г.

Learned many things about computer vision.

автор: Zanuar E R

18 янв. 2022 г.

Good Course, I have learned a lot from it

автор: zhizhen w

10 авг. 2020 г.

a bit too easy for professional engineer

автор: Yu-Chen L

18 июня 2020 г.

Maybe could be better with more content.

автор: Shankar K M

10 февр. 2020 г.

Very repetitive examples and howe works.

автор: rajesh t

12 янв. 2020 г.

Need more depth and real life scenarios.

автор: Vaidic J

25 мая 2020 г.

little more explanations were required

автор: Muthiah A

5 янв. 2020 г.

Useful continuation for practitioner.

автор: Saniya S

25 мая 2020 г.

Assignment submission was very slow.

автор: Renato R

5 янв. 2020 г.

needs to be more advanced too basic