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Comentários e feedback de alunos de Convolutional Neural Networks in TensorFlow da instituição deeplearning.ai

4.7
estrelas
6,983 classificações
1,087 avaliações

Sobre o curso

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....

Melhores avaliações

MS
12 de Nov de 2020

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!

RB
14 de Mar de 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..

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976 — 1000 de 1,088 Avaliações para o Convolutional Neural Networks in TensorFlow

por ABHAS B

9 de Abr de 2020

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

por Ameya D

17 de Jun de 2020

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

por Amit C

18 de Mar de 2020

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

por Jingwei L

30 de Ago de 2019

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

por Harri V

26 de Jan de 2021

Week 4 final assignment was quite bad, because there was new Python/Numpy stuff which was not covered at all in the course.

por Marc-Antoine G

13 de Nov de 2019

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

por Samuel K

2 de Nov de 2019

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

por Daniel D

26 de Mar de 2020

Pros: the course teaches CNNs clearly and concisely.

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

por David H

16 de Nov de 2019

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

por Shreenivas

22 de Dez de 2020

Good content. The coding and assignments need significant improvement. There is no support whatsoever in assignments.

por Sailesh G

2 de Nov de 2019

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

por Daniel Y

27 de Fev de 2021

Disappointing. This is more like Python course. Deep Learning specialization CNN course teaches you x100 more.

por Mohammed F

6 de Jul de 2019

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

por Alexey V

22 de Nov de 2019

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

por Shubham A G

25 de Ago de 2019

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

por Frank W

17 de Jul de 2020

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

por Michael E

14 de Fev de 2020

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

por Apichart L

5 de Jul de 2021

Not well-design, it is very light information and knowledge to learn, unlike the #1 introduction.

por Nahum P

22 de Set de 2020

Final work had almost no connection to what you learned during the course.

Not enough hands on.

por ROSS

15 de Out de 2021

The knowledge taught in the course is over-simplified. The assignments are not well-designed.

por Geoff G

17 de Ago de 2020

The topics are explained very briefly.There is no in depth coverage of the mentioned topics

por Yu S C

26 de Jun de 2021

I dont think this course is very helpful in terms of price/how much you can learn.

por Sajal C

31 de Mar de 2020

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

por Javier I R

15 de Nov de 2020

Great course, but the last exam was miles away from the things presented on it.

por Ashish J

3 de Jul de 2020

this could have been better if object detection and segmentation was a part of