Skip to Content
Deep Learning with Applications Using Python: Chatbots and Face, Object, and Speech Recognition With TensorFlow and Keras
book

Deep Learning with Applications Using Python: Chatbots and Face, Object, and Speech Recognition With TensorFlow and Keras

by Navin Kumar Manaswi
April 2018
Intermediate to advanced content levelIntermediate to advanced
228 pages
3h 41m
English
Apress
Content preview from Deep Learning with Applications Using Python: Chatbots and Face, Object, and Speech Recognition With TensorFlow and Keras
©  Navin Kumar Manaswi 2018
Navin Kumar ManaswiDeep Learning with Applications Using Python https://doi.org/10.1007/978-1-4842-3516-4_2

2. Understanding and Working with Keras

Navin Kumar Manaswi1 
(1)
Bangalore, Karnataka, India
 

Keras is a compact and easy-to-learn high-level Python library for deep learning that can run on top of TensorFlow (or Theano or CNTK). It allows developers to focus on the main concepts of deep learning, such as creating layers for neural networks, while taking care of the nitty-gritty details of tensors, their shapes, and their mathematical details. TensorFlow (or Theano or CNTK) has to be the back end for Keras. You can use Keras for deep learning applications without interacting with the relatively complex TensorFlow ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Applied Deep Learning with TensorFlow 2: Learn to Implement Advanced Deep Learning Techniques with Python

Applied Deep Learning with TensorFlow 2: Learn to Implement Advanced Deep Learning Techniques with Python

Umberto Michelucci
Deep Learning with TensorFlow 2 and Keras - Second Edition

Deep Learning with TensorFlow 2 and Keras - Second Edition

Antonio Gulli, Dr. Amita Kapoor, Sujit Pal
Python Deep Learning Projects

Python Deep Learning Projects

Matthew Lamons, Rahul Kumar, Abhishek Nagaraja

Publisher Resources

ISBN: 9781484235164Purchase LinkPublisher Website