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

4.7
estrelas
7,387 classificações
1,150 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

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..

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!

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1076 — 1100 de 1,152 Avaliações para o Convolutional Neural Networks in TensorFlow

por Victor S

4 de set de 2020

Useful course. Just a bit unstructured.

por Param O

30 de jul de 2021

The grader keeps running out of memory

por Bojiang J

7 de mar de 2020

Content too easy and not engaging....

por Jorge E

22 de set de 2021

Se repiten varios temas del curso 1

por Aymen M

20 de mar de 2021

The last assignment is malformed

por Navid H

15 de set de 2019

I wish it had real assignments

por Samyak J

2 de ago de 2020

exercises are not very clear

por Paula S

6 de abr de 2020

course is a little too easy.

por Pallavi

12 de mar de 2020

It was not great and good

por Yuxuan C

12 de abr de 2020

A little bit too easy.

por Luiz C

11 de jun de 2019

not challenging enough

por Victor M

19 de mar de 2020

Contenido superficial

por Igors K

26 de out de 2019

I wish it used TF2.

por Masoud V

21 de ago de 2019

Useful but too easy

por Ruxue P

14 de out de 2020

Too little content

por Gerard C I

20 de nov de 2019

to much shallow

por Rob S

3 de set de 2020

Good course

por Nechi A

29 de nov de 2020

too basic

por Md I A

21 de set de 2020

just ok

por Thomas R

8 de fev de 2021

Materials were good for someone who has taken university courses on convolutional networks, but labs were extremely poorly done. Final lab of the course was missing sections for the data generator flow method calls, and augmentation wasn't even tested for. Marker could be improved and provided code can have better sections and maybe an explaining markdown at the top rather than going back and forth. I also noticed that accuracy changed from logs.get('acc') to logs.get('accuracy') which seems to be a tensorflow version issue. I feel overall like the course has been abandoned.

por Li P Z

19 de jan de 2020

If you have taken Andrew's courses in ML or deep learning, you will be disappointed. The amount of content in the videos and exercises is shrunk down by 75% per week. I think a much better job could have been done of structuring the course, and creating meaningful exercises. The instructor does an OK job of showing you how to use TF, but he doesn't always explain things very clearly, and doesn't always have an accurate understanding of how ML or deep learning works.

por 黃文喜

7 de jun de 2020

Content is really useful, but the assignment is really really bad and not user friendly(actually it drives me crazy). For example, instruction is not clear, parameter is outdated(still use 'acc' for accuracy?), assignment cannot be graded not because of modeling. These inconvenience obscure of the importance of learning CNN in TF. For this reason I don't think this course worth more than 3 stars.

por Rishi R

26 de jul de 2020

This course could have covered many more topics in detail, like visualizing individual layers, performing style transfer, saving and loading models, etc. All these were skipped and weeks were wasted on a simple extension of a small concept (image augmentation and multi-class learning) which anyone who glanced at the Keras API could have learnt. I am disappointed at this course frankly.

por Tran N M T

5 de jul de 2020

Really a bad course. Most of the materials can be found online for free on TensorFlow official documentations. Many practices are outdated. Problems with the coding assignment are a nightmare. There is no supervisor to answer many common questions. The code grader checks for very particular things and instructions were not clear at all. In general, this is a pretty bad course.

por Ayush M

8 de dez de 2020

Course Material not detailed enough and expected more from it. It does not contain enough variety in exercises and lacks a lot of concepts.

Anyone with good learning (and "overfitting") can complete 1 course in a day.

Final assignment lacked a lot of use case description and it did not even tell us anything about the data or recommended parameters for training.