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Вернуться к Convolutional Neural Networks in TensorFlow

Отзывы учащихся о курсе Convolutional Neural Networks in TensorFlow от партнера deeplearning.ai

4.7
звезд
Оценки: 6,937
Рецензии: 1,081

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 deeplearning.ai 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 deeplearning.ai 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

JM
11 сент. 2019 г.

great introductory stuff, great way to keep in touch with tensorflow's new tools, and the instructor is absolutely phenomenal. love the enthusiasm and the interactions with andrew are a joy to watch.

RB
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..

Фильтр по:

801–825 из 1,081 отзывов о курсе Convolutional Neural Networks in TensorFlow

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.

автор: Brian ( B

23 окт. 2019 г.

very practical courses on implementation of CNN in tensorflow. Suggest student also take the deeplearning series with this series.

автор: revant t

20 мая 2020 г.

Programming assignments could have been better. The programming assignments at the end of each week were not challenging enough.

автор: Hang N

26 февр. 2020 г.

This course offers more executable functions than actually helping you understand (in-depth) how neural network really works.

автор: Parikshit N

12 июля 2021 г.

Good content and Lawrences technique was great. But it took a bit longer where assistance was required during assignments.

автор: Przemysław D

27 сент. 2019 г.

Instructors are really good, but in my opinion, this course should contain Object Detection and Object Segmentation topis.

автор: Balaji K

7 авг. 2020 г.

Short, crisp and to-the-point discussions... Complex practice exercises designed as easy ones for learners. Well done !

автор: Bhabani D

5 янв. 2020 г.

Great introductory course to learn the application of TensorFlow with Keras in the field of Convolutional Neural Network.

автор: Ricardo F

31 мар. 2020 г.

Excelent course! The examples could be more elaborated, but this is a minor issue. Congratulations, and thanks a lot!

автор: Benjamin S

12 окт. 2020 г.

A lot of learning material to digest but at the the end of the course you really have the feeling you've progressed.

автор: Ibrahim M

6 мая 2021 г.

Programming assignments need a little more comments and illustration to save more time. But it still amazing course

автор: Wiput T

29 июля 2020 г.

It the great course and good explainataion. Tensorflow 2.0 is quite good for quick development tool for AIT project

автор: Brian D O

11 мар. 2021 г.

The lectures are great but some of the programming assignments deviate from the code taught and lack guidance.

автор: Josian Q

1 мая 2020 г.

Overall it was really good. Some of the code needed tweaking and the final test was not so easy to get right.

автор: Jaap d V

11 мар. 2020 г.

Thank for a great course. Please make the code samples it work for TF2.X the TF1.X has run out of shelf life

автор: Kevin H

12 апр. 2020 г.

End assignment uses skills not practiced in the course itself. Otherwise very smooth and well presented.

автор: Carlos D R

14 февр. 2020 г.

Es una gran continuación al curso anterior. No se puede hacer sin haber hecho previamente el otro curso

автор: Arpit G

7 янв. 2021 г.

Good and clear explanation of the basic concepts . But assignements quality can be certainly improved.

автор: Dr P M P

19 дек. 2019 г.

Course is good to start but it should include other aspects of neural network than image processing.

автор: Muhammad A B

18 окт. 2020 г.

This was hard, but I feel like I'm getting the hang of it. First course now feels awfully easy lol!

автор: Yeo L K

18 окт. 2020 г.

A little too simple, would appreciate a deeper dive into the classes and methods of the tf library.

автор: ERIC W D S

21 июля 2020 г.

This rate refers to my global opinion. I had some trouble in the third week project send. Thanks.

автор: Sai S V K

28 июня 2020 г.

Assignments could be a little more tedious. Over all explanation of content in the course is good

автор: Antoine A

2 янв. 2021 г.

Good course overall, but the exercise of the end of week 4 was really badly conceived/explained

автор: Ana C

25 янв. 2020 г.

Very interesting course. I've learned a lot. I would like to have a little more advanced topics