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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
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Оценки: 4,759
Рецензии: 715

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

RB

Mar 15, 2020

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..

JM

Sep 12, 2019

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.

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651–675 из 712 отзывов о курсе Convolutional Neural Networks in TensorFlow

автор: Amir S

May 25, 2020

Course assignments need a good overhaul. The two environments to practice the assignments (Jupyter workbooks and Google Colab) are not consistent, one throws an error while the other one works fine.

автор: Nermeen M

Dec 13, 2019

Very good course but please consider reordering the videos and reading especially in week 3. It is better to discuss the code in the video before moving to the notebook not the opposite.

Thank you

автор: Ashok N

Jun 26, 2020

Course content was super nice.

But exercise organization is very annoying. not at all satisfied with the exercises. sometimes not loading and sometimes is really annoying . very disappointed

автор: Renjith B

Jul 15, 2019

Good content for classification tasks. But didn't cover anything related to object recognition, localisation and semantic segmentation which are the challenging computer vision tasks.

автор: Yuvraj G

Apr 11, 2020

Too basic course. If its a practical course, then there should be exposure to more functionality of keras and not just the basic one which can be done from a blog/documentation.

автор: Andrea B

Jun 01, 2020

the topic is interesting, and the course is quite hands-on, but the treatment of the subject is extremely basic. Videos are too short and somehow superficial and incomplete

автор: Adnan

Jun 08, 2020

It was a great course, but in my opinion, it could have been even better if it involved more concepts & APIs to explore apart from the most in-use TensorFlow APIs.

автор: Ethan V

Aug 17, 2019

Solid content, but it feels like it's not *very* much on top of the first course in this specialization. I think these two courses could be combined into one.

автор: Madhav A

Oct 16, 2019

The course is good for beginners as it is very basic. It needs more advance topics like Detection using TensorFlow. Have a lot of scope for improvement.

автор: Alejandro B G

Sep 03, 2019

Google colab system for tasks is pretty bad, no control on the tasks plus it erases and u can't prove you did the work unless you save it

автор: ABHAS B

Apr 09, 2020

The course content is excellent. The talks with Andrew are inspiring, but the assignment graders are aweful and a big turn off.

автор: Ameya D

Jun 17, 2020

This course is more of hands on activity in tensorflow. You need to have good understanding of CNN prior to doing this course.

автор: Amit C

Mar 18, 2020

Content is very limited.I wish they could have gone in-depth covered more areas of CNN like object detection ,segmentation etc

автор: Jingwei L

Aug 30, 2019

The course is taught excellently. However, there are overfull file stream operations in Python that the course does not cover.

автор: Marc-Antoine G

Nov 13, 2019

Please make the "Ungraded assignment" Graded and add more comments/directive in them to make sure we understand each steps.

автор: Samuel K

Nov 02, 2019

Clear explanations. Good sample codes. Too easy. Doesn't go deep enough in terms of theory. Exercises should be mandatory.

автор: Daniel D

Mar 26, 2020

Pros: the course teaches CNNs clearly and concisely.

Cons: the memory issues on the last assignment wasted a lot of time.

автор: David H

Nov 17, 2019

Not solid enough and the exercise could be more organised. For example: some of the data downloading links didn't work.

автор: Sailesh G

Nov 02, 2019

Expected a lot more in this course from the Tensorflow specialization. Something that'd take us beyond tf.keras.

автор: Mohammed F

Jul 06, 2019

Could have dived more into the details and inner workings of Convolutional layers but overall awesome course.

автор: Aleksey V

Nov 22, 2019

complex ideas in very basic tasks that you can easily accomplish by copy-pasting from provided notebooks.

автор: Shubham A G

Aug 25, 2019

Lacks depth and complexity. The course is geared more towards complete newbies or high school graduates.

автор: Frank W

Jul 17, 2020

The programming tasks are not very helpful. The main difficulty is that unknown methods should be used.

автор: Michael E

Feb 14, 2020

Would like to have seen some information on techniques such as batch normalization and residual layers.

автор: Sajal C

Mar 31, 2020

Course is good however there can be programming assignments for better practice.