Chevron Left
Вернуться к Convolutional Neural Networks in TensorFlow

Отзывы учащихся о курсе Convolutional Neural Networks in TensorFlow от партнера

Оценки: 5,761
Рецензии: 873

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 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....

Лучшие рецензии

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.

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:

826–850 из 867 отзывов о курсе Convolutional Neural Networks in TensorFlow

автор: Mikołaj M

12 окт. 2020 г.

The course covers elementary techniques.

автор: Victor S

4 сент. 2020 г.

Useful course. Just a bit unstructured.

автор: Bojiang J

7 мар. 2020 г.

Content too easy and not engaging....

автор: Navid H

15 сент. 2019 г.

I wish it had real assignments

автор: Samyak J

2 авг. 2020 г.

exercises are not very clear

автор: Paula S

6 апр. 2020 г.

course is a little too easy.

автор: Pallavi

12 мар. 2020 г.

It was not great and good

автор: Yuxuan C

12 апр. 2020 г.

A little bit too easy.

автор: Luiz C

11 июня 2019 г.

not challenging enough

автор: Victor M

19 мар. 2020 г.

Contenido superficial

автор: Igors K

26 окт. 2019 г.

I wish it used TF2.

автор: Masoud V

21 авг. 2019 г.

Useful but too easy

автор: Ruxue P

14 окт. 2020 г.

Too little content

автор: Gerard C I

20 нояб. 2019 г.

to much shallow

автор: Rob S

3 сент. 2020 г.

Good course

автор: Mohammed I A T

21 сент. 2020 г.

just ok

автор: Li P Z

19 янв. 2020 г.

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.

автор: 黃文喜

7 июня 2020 г.

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.

автор: Rishi R

26 июля 2020 г.

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.

автор: Tran N M T

5 июля 2020 г.

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.

автор: Daniel N

13 авг. 2020 г.

Far to simple. Significant concepts were glossed over and the exercises were mainly copy and past from the examples. Lessons that covered a "week" took < 1 hour with a couple minor points learned. Don't recommend if you want to really know how CNNs work.

автор: Dhruva G

21 авг. 2019 г.

The content could have been covered in 15 min. Moreover, I thought you guys will teach tensorflow low level API and estimators etc. atleast in course 2. Also, what happened to the graded assignments ? I finished this course in 40 min.

автор: Stephen M

4 мая 2020 г.

The course simply does not cover much information. The whole course could be compacted into a decent one hour lecture. Andrew Ng has some great courses on machine learning but I don't believe this to be one of them.

автор: Jose R

26 июля 2020 г.

No enough time spend in the actual code which limits the learning on the understanding of the concepts with implementation. Doubt how useful this is

автор: Serebrianskii D

12 нояб. 2020 г.

Absolutely awful grader. You spend most of the time figuring out errors and intentions of the grader writer.