Bộ sách luyện thi ETS 2023 LC&RC
199,000₫
299,000₫
Sách keo gáy, bìa mềm
Thể loại:Computers - Computer Science
Năm:2020
In lần thứ:1
Ngôn ngữ:english
Trang:473 / 467
Apply computer vision and machine learning
concepts in developing business and industrial applications using a
practical, step-by-step approach.
The book comprises four main
sections starting with setting up your programming environment and
configuring your computer with all the prerequisites to run the code
examples. Section 1 covers the basics of image and video processing with
code examples of how to manipulate and extract useful information from
the images. You will mainly use OpenCV with Python to work with examples
in this section.
Section 2 describes machine learning and neural
network concepts as applied to computer vision. You will learn
different algorithms of the neural network, such as convolutional neural
network (CNN), region-based convolutional neural network (R-CNN), and
YOLO. In this section, you will also learn how to train, tune, and
manage neural networks for computer vision. Section 3 provides
step-by-step examples of developing business and industrial
applications, such as facial recognition in video surveillance and
surface defect detection in manufacturing.
The final section is
about training neural networks involving a large number of images on
cloud infrastructure, such as Amazon AWS, Google Cloud Platform, and
Microsoft Azure. It walks you through the process of training
distributed neural networks for computer vision on GPU-based cloud
infrastructure. By the time you finish reading Building Computer Vision Applications Using Artificial Neural Networks
and working through the code examples, you will have developed some
real-world use cases of computer vision with deep learning.
What You Will Learn
· Employ image processing, manipulation, and feature extraction techniques
· Work with various deep learning algorithms for computer vision
· Train, manage, and tune hyperparameters of CNNs and object detection models, such as R-CNN, SSD, and YOLO
· Build neural network models using Keras and TensorFlow
· Discover best practices when implementing computer vision applications in business and industry
· Train distributed models on GPU-based cloud infrastructure
Who This Book Is For
Data scientists, analysts, and machine learning and software engineering professionals with Python programming knowledge.
