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ROS Robotics Projects,

You're reading from   ROS Robotics Projects, Build and control robots powered by the Robot Operating System, machine learning, and virtual reality

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Product type Paperback
Published in Dec 2019
Publisher Packt
ISBN-13 9781838649326
Length 456 pages
Edition 2nd Edition
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Author (1):
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Ramkumar Gandhinathan Ramkumar Gandhinathan
Author Profile Icon Ramkumar Gandhinathan
Ramkumar Gandhinathan
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Table of Contents (14) Chapters Close

Preface 1. Getting Started with ROS FREE CHAPTER 2. Introduction to ROS-2 and Its Capabilities 3. Building an Industrial Mobile Manipulator 4. Handling Complex Robot Tasks Using State Machines 5. Building an Industrial Application 6. Multi-Robot Collaboration 7. ROS on Embedded Platforms and Their Control 8. Reinforcement Learning and Robotics 9. Deep Learning Using ROS and TensorFlow 10. Creating a Self-Driving Car Using ROS 11. Teleoperating Robots Using a VR Headset and Leap Motion 12. Face Detection and Tracking Using ROS, OpenCV, and Dynamixel Servos 13. Other Books You May Enjoy

Introduction to deep learning and its applications

What actually is deep learning? It is a buzzword in neural network technology. What is a neural network then? An artificial neural network is a computer software model that replicates the behavior of neurons in the human brain. A neural network is one way to classify data. For example, if we want to classify an image based on whether it contains an object or not, we can use this method.

There are several other computer software models for classification such as logistic regression and Support Vector Machine (SVM); a neural network is one of them. So, why are we not calling it a neural network instead of deep learning? The reason is that, in deep learning, we use a large number of artificial neural networks. So, you may ask, why was it not possible before? The answer is: to create a large number of neural networks (multilayer perceptron...

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