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Отзывы учащихся о курсе Convolutional Neural Networks in TensorFlow от партнера

Оценки: 5,237
Рецензии: 794

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


Sep 12, 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.


Mar 15, 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..

Фильтр по:

626–650 из 790 отзывов о курсе Convolutional Neural Networks in TensorFlow

автор: Lei W

Oct 30, 2019

will be nice to have non-third party programming exercises that are graded by Coursera

автор: Donal B

Oct 18, 2019

Excellent course. Would have liked graded coding assignments like in the first course.

автор: Eduardo Z

Jun 24, 2020

Great! Had some difficulties with the last excercise. But the rest was OK. Thanks!

автор: Phuoc H L

Nov 14, 2019

More exercises should be available for students to practice and test their skills.

автор: Eran Y

Jun 20, 2020

Some references to relevant code in tests would be nice, don't send me searching.

автор: Gregor F

Jan 07, 2020

Straight to point with a lot of useful techniques! Interesting examples as well.


Aug 26, 2020

Nice course to learn about the basics about how to implement CNN's with keras.

автор: Sebastian M A

Dec 06, 2019

No le pongo las 5 estrellas por la falta de ejercicios prácticos calificables.

автор: Arun P R

Apr 18, 2020

Need to more specific about the instructions given for Programming Assignment

автор: Damon W

Oct 08, 2019

Good practical course. A bit heavy on visual images, but very informative.

автор: Ma Y

Jun 19, 2020

Excellent materials and assignments! May be lectures can be a bit longer.

автор: Shaun M

Feb 23, 2020

greaded assignments are needed as they help to understand the code better

автор: Ruben A M

Aug 20, 2020

the course is good, however, I feel that the content is stretched a lot.

автор: Prashant

Aug 28, 2020

Last week excercise was a little bit challenging ,overall great course.

автор: vikas l

Jun 07, 2020

This Covers pretty well more than basics and dig little deep into CNNs.

автор: Ahmed K M

May 19, 2020

Focusing more on the code for python beginners would be much better!

автор: Rishabh B

Feb 01, 2020

Could have had tougher exercises. Great basics course nevertheless!

автор: Xiangzhen Z

Aug 18, 2019

a little bit too easy compared to Andrew Ng's deep learning course.

автор: Zhou D

Jun 19, 2019

actually I hope there will be the implementation of detection task

автор: Amardeep S

Dec 29, 2019

The homework assignments should be required and more challenging

автор: Sharvil G

Aug 06, 2019

Transfer learning part should have been in more detail. Thanks.

автор: Ifrah M

May 14, 2020

A little bit of more explanation of the notebooks are required

автор: Muhammad U

Aug 18, 2019

A well taught course with interesting coursework and projects

автор: Bethel R H

May 11, 2020

One of the best courses offered by community

автор: Adnan Q

May 04, 2020

Very good course dealing with image convolutions and CNN