Practical Convolutional Neural Networks
This book helps you master CNN, from the basics to the most advanced concepts in CNN such as GANs, instance classification and attention mechanism for vision models and more. You will implement advanced CNN models using complex image and video datasets. By the end of the book you will learn CNN’s best practices to implement smart ConvNet models and apply them to solve complex deep learning problems.
Offered by
Difficulty Level
Intermediate
Completion Time
7h16m
Language
English
About Book
Who Is This Book For?
This book is for data scientists, machine learning and deep learning practitioners, Cognitive and Artificial Intelligence enthusiasts who want to move one step further in building Convolutional Neural Networks. Get hands-on experience with extreme datasets and different CNN architectures to build efficient and smart ConvNet models. Basic knowledge of deep learning concepts and Python programming language is expected.
Practical Convolutional Neural Networks
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 7h16m total length
Deep Neural Networks - Overview
Introduction to Convolutional Neural Networks
Build Your First CNN and Performance Optimization
Popular CNN Model's Architectures
Transfer Learning
Autoencoders for CNN
Object Detection with CNN
Generative Adversarial Network
Visual Attention Based CNN
Related Resources
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