Pro Deep Learning with TensorFlow 2.0: A Mathematical Approach to Advanced Artificial Intelligence in Python

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2023

S. PattanayakPro Deep Learning with TensorFlow 2.0https://doi.org/10.1007/978-1-4842-8931-0_3

3. Convolutional Neural Networks

Santanu Pattanayak¹  

(1)

Prestige Ozone, Bangalore, Karnataka, India

 

Artificial neural networks have flourished in recent years in the processing of unstructured data, especially images, text, audio, and speech. Convolutional neural networks (CNNs) work best for such unstructured data. Whenever there is a topology associated with the data, convolutional neural networks do a good job of extracting the important features out of the data. From an architectural perspective, CNNs are inspired by multi-layer Perceptrons. By imposing local ...