Artificial Vision and Language Processing for Robotics: Create end-to-end systems that can power robots with artificial vision and
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Bester Preis: € 20,41 (vom 07.06.2019)1
Artificial Vision and Language Processing for Robotics
EN NW EB DLISBN: 9781838557669 bzw. 1838557660, in Englisch, neu, E-Book, elektronischer Download.
Lieferung aus: Vereinigte Staaten von Amerika, In Stock, plus shipping.
Create end-to-end systems that can power robots with artificial vision and deep learning techniques Key Features Study ROS, the main development framework for robotics, in detail Learn all about convolutional neural networks, recurrent neural networks, and robotics Create a chatbot to interact with the robot Book Description Artificial Vision and Language Processing for Robotics begins by discussing the theory behind robots. You'll compare different methods used to work with robots and explore computer vision, its algorithms, and limits. You'll then learn how to control the robot with natural language processing commands. You'll study Word2Vec and GloVe embedding techniques, non-numeric data, recurrent neural network (RNNs), and their advanced models. You'll create a simple Word2Vec model with Keras, as well as build a convolutional neural network (CNN) and improve it with data augmentation and transfer learning. You'll study the ROS and build a conversational agent to manage your robot. You'll also integrate your agent with the ROS and convert an image to text and text to speech. You'll learn to build an object recognition system using a video. By the end of this book, you'll have the skills you need to build a functional application that can integrate with a ROS to extract useful information about your environment. What you will learn Explore the ROS and build a basic robotic system Understand the architecture of neural networks Identify conversation intents with NLP techniques Learn and use the embedding with Word2Vec and GloVe Build a basic CNN and improve it using generative models Use deep learning to implement artificial intelligence(AI)and object recognition Develop a simple object recognition system using CNNs Integrate AI with ROS to enable your robot to recognize objects Who this book is for Artificial Vision and Language Processing for Robotics is for robotics engineers who want to learn how to integrate computer vision and deep learning techniques to create complete robotic systems. It will prove beneficial to you if you have working knowledge of Python and a background in deep learning. Knowledge of the ROS is a plus.
Create end-to-end systems that can power robots with artificial vision and deep learning techniques Key Features Study ROS, the main development framework for robotics, in detail Learn all about convolutional neural networks, recurrent neural networks, and robotics Create a chatbot to interact with the robot Book Description Artificial Vision and Language Processing for Robotics begins by discussing the theory behind robots. You'll compare different methods used to work with robots and explore computer vision, its algorithms, and limits. You'll then learn how to control the robot with natural language processing commands. You'll study Word2Vec and GloVe embedding techniques, non-numeric data, recurrent neural network (RNNs), and their advanced models. You'll create a simple Word2Vec model with Keras, as well as build a convolutional neural network (CNN) and improve it with data augmentation and transfer learning. You'll study the ROS and build a conversational agent to manage your robot. You'll also integrate your agent with the ROS and convert an image to text and text to speech. You'll learn to build an object recognition system using a video. By the end of this book, you'll have the skills you need to build a functional application that can integrate with a ROS to extract useful information about your environment. What you will learn Explore the ROS and build a basic robotic system Understand the architecture of neural networks Identify conversation intents with NLP techniques Learn and use the embedding with Word2Vec and GloVe Build a basic CNN and improve it using generative models Use deep learning to implement artificial intelligence(AI)and object recognition Develop a simple object recognition system using CNNs Integrate AI with ROS to enable your robot to recognize objects Who this book is for Artificial Vision and Language Processing for Robotics is for robotics engineers who want to learn how to integrate computer vision and deep learning techniques to create complete robotic systems. It will prove beneficial to you if you have working knowledge of Python and a background in deep learning. Knowledge of the ROS is a plus.
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Artificial Vision and Language Processing for Robotics - Create end-to-end systems that can power robots with artificial vision and deep learning techniques
~EN NW EB DLISBN: 9781838557669 bzw. 1838557660, vermutlich in Englisch, Packt Publishing, neu, E-Book, elektronischer Download.
Lieferung aus: Deutschland, Free shipping.
Artificial Vision and Language Processing for Robotics: Create end-to-end systems that can power robots with artificial vision and deep learning techniquesKey FeaturesStudy ROS, the main development framework for robotics, in detailLearn all about convolutional neural networks, recurrent neural networks, and roboticsCreate a chatbot to interact with the robotBook DescriptionArtificial Vision and Language Processing for Robotics begins by discussing the theory behind robots. You`ll compare different methods used to work with robots and explore computer vision, its algorithms, and limits. You`ll then learn how to control the robot with natural language processing commands. You`ll study Word2Vec and GloVe embedding techniques, non-numeric data, recurrent neural network (RNNs), and their advanced models. You`ll create a simple Word2Vec model with Keras, as well as build a convolutional neural network (CNN) and improve it with data augmentation and transfer learning. You`ll study the ROS and build a conversational agent to manage your robot. You`ll also integrate your agent with the ROS and convert an image to text and text to speech. You`ll learn to build an object recognition system using a video.By the end of this book, you`ll have the skills you need to build a functional application that can integrate with a ROS to extract useful information about your environment.What you will learnExplore the ROS and build a basic robotic systemUnderstand the architecture of neural networksIdentify conversation intents with NLP techniquesLearn and use the embedding with Word2Vec and GloVeBuild a basic CNN and improve it using generative modelsUse deep learning to implement artificial intelligence(AI)and object recognitionDevelop a simple object recognition system using CNNsIntegrate AI with ROS to enable your robot to recognize objectsWho this book is forArtificial Vision and Language Processing for Robotics is for robotics engineers who want to learn how to integrate computer vision and deep learning techniques to create complete robotic systems. It will prove beneficial to you if you have working knowledge of Python and a background in deep learning. Knowledge of the ROS is a plus. Englisch, Ebook.
Artificial Vision and Language Processing for Robotics: Create end-to-end systems that can power robots with artificial vision and deep learning techniquesKey FeaturesStudy ROS, the main development framework for robotics, in detailLearn all about convolutional neural networks, recurrent neural networks, and roboticsCreate a chatbot to interact with the robotBook DescriptionArtificial Vision and Language Processing for Robotics begins by discussing the theory behind robots. You`ll compare different methods used to work with robots and explore computer vision, its algorithms, and limits. You`ll then learn how to control the robot with natural language processing commands. You`ll study Word2Vec and GloVe embedding techniques, non-numeric data, recurrent neural network (RNNs), and their advanced models. You`ll create a simple Word2Vec model with Keras, as well as build a convolutional neural network (CNN) and improve it with data augmentation and transfer learning. You`ll study the ROS and build a conversational agent to manage your robot. You`ll also integrate your agent with the ROS and convert an image to text and text to speech. You`ll learn to build an object recognition system using a video.By the end of this book, you`ll have the skills you need to build a functional application that can integrate with a ROS to extract useful information about your environment.What you will learnExplore the ROS and build a basic robotic systemUnderstand the architecture of neural networksIdentify conversation intents with NLP techniquesLearn and use the embedding with Word2Vec and GloVeBuild a basic CNN and improve it using generative modelsUse deep learning to implement artificial intelligence(AI)and object recognitionDevelop a simple object recognition system using CNNsIntegrate AI with ROS to enable your robot to recognize objectsWho this book is forArtificial Vision and Language Processing for Robotics is for robotics engineers who want to learn how to integrate computer vision and deep learning techniques to create complete robotic systems. It will prove beneficial to you if you have working knowledge of Python and a background in deep learning. Knowledge of the ROS is a plus. Englisch, Ebook.
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Artificial Vision and Language Processing for Robotics: Create end-to-end systems that can power robots with artificial vision and
~EN NW EBISBN: 9781838557669 bzw. 1838557660, vermutlich in Englisch, Packt Publishing, neu, E-Book.
Lieferung aus: Vereinigte Staaten von Amerika, In Stock.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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