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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
звезд
Оценки: 7,339
Рецензии: 1,140

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

MS

12 нояб. 2020 г.

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 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:

226–250 из 1,142 отзывов о курсе Convolutional Neural Networks in TensorFlow

автор: Gustavo A

10 авг. 2019 г.

I enjoyed this course a lot, but I missed the code evaluation step. On the other hand, the content was as good as it has been.

автор: Dustin Z

27 июня 2020 г.

Fun course. A good balance of easy and challenging material. The lessons based primarily on notebooks, and are very hands-on.

автор: Jay H

15 июня 2020 г.

It was a very helpful course. The discussions forum help a bit. Maybe, more questions asked or answers could help even more.

автор: Diego O S

12 янв. 2021 г.

Really clear and with the exact amount of examples. (I would like to see more examples and not only the ones seen in class)

автор: VAGHELA H N S

18 июня 2020 г.

course is well designed. The codes and notebooks provided in the course can be very much helpful for any beginner to learn.

автор: Tze C L

18 июня 2020 г.

Very insightful and involving course that teaches you how to perform image classification with Convolution Neural Networks.

автор: Marcin Ś

30 авг. 2021 г.

Pretty good introduction to CNNs with Tensorflow. Great idea with exercise assignments to finish milestones in the course!

автор: Bonthu S

22 апр. 2021 г.

Simply the best course to implement convolution neural network in tensorflow but don't look for deep understanding of CNN.

автор: Zarinah C

20 февр. 2021 г.

One of the best online courses I've taken. Well explained, accessible, and references so that you can deep dive as needed.

автор: SRIKANTH T

12 сент. 2020 г.

the course in nice , the explanation given by Laurence Moroney is excellent , so the course is highly recommended to take

автор: Gogul I

22 июня 2019 г.

Amazing course to learn concepts such as Dropouts, Augmentation and Transfer Learning to solve real world image problems.

автор: Farid A

18 мая 2022 г.

a​wesome teacher

v​ery practical hands-on assignments and excerices

h​elpfull assistants for problem quick problem solving

автор: Márton B

4 июня 2021 г.

I think this is a useful, understandable and practical course. I liked it. The codes in Jupyter notebooks are very good.

автор: João R

23 мар. 2021 г.

It's a great course to get the basics of CNN. The last lab demands some tricks that are covered in the discussion forum.

автор: Carlos S

22 мая 2020 г.

Great course! It actually develops very fast upon the fundamentals covered by Andrew in the Deep Learning Specialization

автор: George D

8 авг. 2019 г.

Very good intro on the subject. Little bit too much hand holding but good overall for complete new folks to the subject.

автор: Rukshan J S

27 апр. 2020 г.

Very well put out course. Gradually increasing the challenge level of exercise is really appreciated! Thanks, Coursera!

автор: sanjay R

25 июля 2019 г.

A very good approach to make beginners feel like home. It's pretty clear and notebooks is also very easy to understand.

автор: sushant p

23 нояб. 2019 г.

Wonderful Course on Convolutional Neural Network Using TF. Having Base knowledge of CNN and DNN Will help immensely !!

автор: Akash S

24 авг. 2020 г.

Amazing! I learnt so many exciting things. Completed 8 weeks in 2 weeks! Can't wait to get to Laurence's next course!

автор: Satyam s

18 апр. 2020 г.

This course has been starting point of my deep learning carrier,

I have learned a lot from this course.

Thanks so much.

автор: Pushpak G

5 сент. 2020 г.

Again a good course which covers a lot of practical implementation of Conv nets and image classification.

Appreciated

автор: Laode M F

26 апр. 2020 г.

Great course to learn computer vision. You'll learn augmentation, transfer learning, and multi class classification.

автор: Peter L

19 мар. 2020 г.

Great grounding so far in tensorflow. Looking forward to cracking on with the next 2 to complete the specialisation.

автор: Thomas M

3 февр. 2021 г.

Good course, coding challenges need more emphasis on the deep learning models, would like to code more from scratch