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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: 5,771
•
Рецензии: 875

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:

376–400 из 868 отзывов о курсе Convolutional Neural Networks in TensorFlow

автор: Michalis F

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25 сент. 2019 г.

simple, to the point and good notebooks! thanks

автор: TEJAS P

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8 июля 2020 г.

Extremely Practical Course ! Really Enriching!

автор: Huajiang L

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16 сент. 2019 г.

Very easy to learn. Very practical and useful!

автор: nilo b m

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13 сент. 2020 г.

Gostei muito do curso, aprendi muitas coisas.

автор: Bohdan K V

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27 авг. 2020 г.

The course is professionally made. Well done!

автор: Abhiroop A

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9 мая 2020 г.

Its an amazing course. 10/10 would recommend

автор: Demaison F

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5 мая 2020 г.

progressif et complet. Exercices intéressants

автор: Gursimran S

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6 янв. 2020 г.

very very useful and powerful toll i learn :)

автор: Pham C B

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29 мая 2020 г.

good course for understand cnn in tensorflow

автор: Sabila H

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1 мая 2020 г.

Great, but the code exercise must be updated

автор: Matas U

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27 апр. 2020 г.

Amazing course, challenging and interesting.

автор: NITIN S T

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21 нояб. 2020 г.

Excellently instructed by Laurence Moroney.

автор: Abid H

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3 июля 2020 г.

Great experience learning this course.Bravo

автор: YASH N

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25 июня 2020 г.

Explained each and every details with ease.

автор: Charley L

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19 апр. 2020 г.

comprehensive concepts, easy to understand.

автор: Antti R

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2 нояб. 2019 г.

Very informative, nice pace, easy to follow

автор: Aashutosh K J

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19 окт. 2020 г.

Very good teacher that's all I have to say

автор: Mohammad A

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13 июня 2020 г.

assignments should contain some guidelines

автор: Venkataraman R

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11 июня 2020 г.

Learnt a lot in this course. Thanks a lot.

автор: Hanan S A

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3 янв. 2020 г.

code and slides are nice and crystal clear

автор: Leo

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25 июня 2019 г.

Great course for Computer Vision problems!

автор: 张越兴

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24 июля 2020 г.

我太爱你了 吴恩达老师还有google这个老师 我在youyube上看过您的视频！

автор: Mats E

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8 июля 2019 г.

Very good high-level introduction course.

автор: Oleksandr M

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11 июня 2019 г.

It's very clear and useful! Thank you! :)

автор: Rich H

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27 июня 2020 г.

Fantastic! I learned so much!!! Love it!

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