Computer Vision Applications Using Deep Learning with Cnns : With Detailed Examples in Python Using Tensorflow and Kivy by Ahmed Fawzy Gad (2018, Trade Paperback)

Bargain Book Stores (1127386)
99.2% positive Feedback
Price:
US $92.93
Approximately£69.65
+ $16.27 postage
Estimated delivery Fri, 9 May - Tue, 20 May
Returns:
30 days return. Buyer pays for return postage. If you use an eBay delivery label, it will be deducted from your refund amount.
Condition:
New
Practical Computer Vision Applications Using Deep Learning with Cnns: With Detailed Examples in Python Using Tensorflow and Kivy (Paperback or Softback). Condition Guide. Your Privacy. Your source for quality books at reduced prices.

About this product

Product Identifiers

PublisherApress L. P.
ISBN-101484241665
ISBN-139781484241660
eBay Product ID (ePID)9038605442

Product Key Features

Number of PagesXxii, 405 Pages
Publication NameComputer Vision Applications Using Deep Learning with Cnns : With Detailed Examples in Python Using Tensorflow and Kivy
LanguageEnglish
SubjectIntelligence (Ai) & Semantics, Programming / Open Source, Programming Languages / Python
Publication Year2018
TypeTextbook
Subject AreaComputers
AuthorAhmed Fawzy Gad
FormatTrade Paperback

Dimensions

Item Weight28.6 Oz
Item Length10 in
Item Width7 in

Additional Product Features

Number of Volumes1 vol.
IllustratedYes
Table Of Content1. Recognition in Computer Vision.- 2. Artificial Neural Network.- 3. Classification using ANN with Engineered Features.- 4. ANN Parameters Optimization.- 5. Convolutional Neural Networks.- 6. TensorFlow Recognition Application.- 7. Deploying Pre-Trained Models.- 8. Cross-Platform Data Science Applications.Appendix: Uploading Projects to PyPI.
SynopsisDeploy deep learning applications into production across multiple platforms. You will work on computer vision applications that use the convolutional neural network (CNN) deep learning model and Python. This book starts by explaining the traditional machine-learning pipeline, where you will analyze an image dataset. Along the way you will cover artificial neural networks (ANNs), building one from scratch in Python, before optimizing it using genetic algorithms. For automating the process, the book highlights the limitations of traditional hand-crafted features for computer vision and why the CNN deep-learning model is the state-of-art solution. CNNs are discussed from scratch to demonstrate how they are different and more efficient than the fully connected ANN (FCNN). You will implement a CNN in Python to give you a full understanding of the model. After consolidating the basics, you will use TensorFlow to build a practical image-recognition model that you will deploy to a web server using Flask, making it accessible over the Internet. Using Kivy and NumPy, you will create cross-platform data science applications with low overheads. This book will help you apply deep learning and computer vision concepts from scratch, step-by-step from conception to production. What You Will Learn Understand how ANNs and CNNs work Create computer vision applications and CNNs from scratch using Python Follow a deep learning project from conception to production using TensorFlow Use NumPy with Kivy to build cross-platform data science applications Who This Book Is For Data scientists, machine learning and deep learning engineers, software developers.
LC Classification NumberQ334-342

All listings for this product

Buy it now
Any condition
New
Pre-owned
No ratings or reviews yet
Be the first to write a review