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Voltar para Convolutional Neural Networks in TensorFlow

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

6,070 classificações
926 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 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....

Melhores avaliações

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!

11 de Set de 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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826 — 850 de 921 Avaliações para o Convolutional Neural Networks in TensorFlow

por Matías F B

28 de Mai de 2020

The material is good, but there is not much thereof.

The duration of the assignmentsis greatly exaggerated, since most of the lengths for the readings and exercises are wrong.

The course can easily be done in 25% of the official time.

por Dirk H

7 de Nov de 2019

If you have taken the first course of the specialization this class was repetitive at some points. I also did not like that there have not been graded coding problems. I still got some practice and learned some new techniques.

por Wenyu Y

20 de Mar de 2020

The materials about implmentation of transfer learning is helpfu, but again, I think the whole content of the first two courses could be compressed into one week. There're really not too much new things.

por Sumit c

18 de Mai de 2020

some clear instructions should be given for students. In exercise of week 4, there was no specific instruction about using .flow instead of .flow_from_directory, for labels we had to use to_catagorical.

por Amir S

24 de Mai de 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.

por Nermeen M

13 de Dez de 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

por Ashok N

26 de Jun de 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

por Renjith B

15 de Jul de 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.

por Yuvraj G

11 de Abr de 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.

por Ted T

2 de Jan de 2021

Lawrence's lectures were good, but exercises were disconnected from course material. Having to do exercises in Google Colab and then redo in Jupyter notebook was inefficient.

por Andrea B

1 de Jun de 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

por Seif M M

20 de Set de 2020

very good course, but think it needs to go deeper in the functions and tools in tensorflow for conv netwroks, i have the feeling that the course is somehow shallow.

por Adnan P

8 de Jun de 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.

por Ethan V

17 de Ago de 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.

por Madhav A

16 de Out de 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.

por Alejandro B G

3 de Set de 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


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 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.