logo

EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link:  https://ebookbell.com/faq 


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Tensorflow 20 Computer Vision Cookbookimplement Machine Learning Solutions To Overcome Various Computer Vision Challenges Jess Martnez

  • SKU: BELL-56422628
Tensorflow 20 Computer Vision Cookbookimplement Machine Learning Solutions To Overcome Various Computer Vision Challenges Jess Martnez
$ 31.00 $ 45.00 (-31%)

4.1

20 reviews

Tensorflow 20 Computer Vision Cookbookimplement Machine Learning Solutions To Overcome Various Computer Vision Challenges Jess Martnez instant download after payment.

Publisher: Packt Publishing
File Extension: PDF
File size: 6.12 MB
Pages: 541
Author: Jesús Martínez
Language: English
Year: 2021

Product desciption

Tensorflow 20 Computer Vision Cookbookimplement Machine Learning Solutions To Overcome Various Computer Vision Challenges Jess Martnez by Jesús Martínez instant download after payment.

The release of TensorFlow 2.x in 2019 was one of the biggest and most anticipated
events in the deep learning and artificial intelligence arena, because it brought with it
long-overdue improvements to this popular and relevant framework, mainly focused on
simplicity and ease of use.
The adoption of Keras as the official TensorFlow high-level API, the ability to switch back
and forth between eager and graph-based execution (thanks to tf.function), and the
ability to create complex data pipelines with tf.data are just a few of the great additions
that TensorFlow 2.x brings to the table.

Related Products