simic milan (174 résultats)

Etat : As New. Unread book in perfect condition.

Etat : New.

Etat : As New. Unread book in perfect condition.

Etat : New.

Hardcover. Etat : Brand New. 160 pages. 9.75x6.50x0.50 inches. In Stock.

Etat : New.

Etat : As New. Unread book in perfect condition.

Etat : As New. Unread book in perfect condition.

Hardcover. Etat : New. Etat de la jaquette : New. 1st Edition. Princeton University Press, 2010. First edition. First printing. Hardbound. New/New. A pristine unread copy. Comes with archival-quality dust jacket protector. 0.0.

Etat : New.

Paperback. Etat : Brand New. 111 pages. 9.25x6.25x0.25 inches. In Stock.

Kartoniert / Broschiert. Etat : New. &Uumlber den AutorCharles Simic (1938-2023) was a poet, essayist, and translator who won numerous awards, including the Pulitzer Prize, the Griffin Poetry Prize, the Wallace Stevens Award, and a MacArthur Fellowship. From .

Hardcover. Etat : Very Good. Etat de la jaquette : Very Good Dust Jacket. First Edition. 208pp. English edition, limited to 8,000 copies. Very good hardcover with dust jacket, from a private home collection. Binding is tight, sturdy, and square. Previous owner's inscription on front endpaper (from the personal collection of a former airline pilot, appears to be signed from a colleague from JAT), otherwise text and photos appear unmarked and clean. Very lightly dinged corners, unclipped dust jacket has rubbing. Ships same or next business day from Dinkytown in Minneapolis, Minnesota. Due to the size/weight of this book extra charges may apply for international shipping.

Etat : New. In.

Etat : New. In.

Etat : New. 1st ed. 2019 edition NO-PA16APR2015-KAP.

Hardcover. Etat : new. Hardcover. Machine learning has become one of the most prevalent topics in recent years. The application of machine learning we see today is a tip of the iceberg. The machine learning revolution has just started to roll out. It is becoming an integral part of all modern electronic devices. Applications in automation areas like automotive, security and surveillance, augmented reality, smart home, retail automation and healthcare are few of them. Robotics is also rising to dominate the automated world. The future applications of machine learning in the robotics area are still undiscovered to the common readers. We are, therefore, putting an effort to write this edited book on the future applications of machine learning on robotics where several applications have been included in separate chapters. The content of the book is technical. It has been tried to cover all possible application areas of Robotics using machine learning. This book will provide the future vision on the unexplored areas ofapplications of Robotics using machine learning. The ideas to be presented in this book are backed up by original research results. The chapter provided here in-depth look with all necessary theory and mathematical calculations. It will be perfect for laymen and developers as it will combine both advanced and introductory material to form an argument for what machine learning could achieve in the future. It will provide a vision on future areas of application and their approach in detail. Therefore, this book will be immensely beneficial for the academicians, researchers and industry project managers to develop their new project and thereby beneficial for mankind. Original research and review works with model and build Robotics applications using Machine learning are included as chapters in this book. We are, therefore, putting an effort to write this edited book on the future applications of machine learning on robotics where several applications have been included in separate chapters. This book will provide the future vision on the unexplored areas ofapplications of Robotics using machine learning. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Etat : New. 1st ed. 2021 edition NO-PA16APR2015-KAP.

Etat : New. In.

Etat : Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Machine learning has become one of the most prevalent topics in recent years. The application of machine learning we see today is a tip of the iceberg. The machine learning revolution has just started to roll out. It is becoming an integral part of all modern electronic devices. Applications in automation areas like automotive, security and surveillance, augmented reality, smart home, retail automation and healthcare are few of them. Robotics is also rising to dominate the automated world. The future applications of machine learning in the robotics area are still undiscovered to the common readers. We are, therefore, putting an effort to write this edited book on the future applications of machine learning on robotics where several applications have been included in separate chapters. The content of the book is technical. It has been tried to cover all possible application areas of Robotics using machine learning. This book will provide the future vision on the unexplored areas ofapplications of Robotics using machine learning. The ideas to be presented in this book are backed up by original research results. The chapter provided here in-depth look with all necessary theory and mathematical calculations. It will be perfect for laymen and developers as it will combine both advanced and introductory material to form an argument for what machine learning could achieve in the future. It will provide a vision on future areas of application and their approach in detail. Therefore, this book will be immensely beneficial for the academicians, researchers and industry project managers to develop their new project and thereby beneficial for mankind. Original research and review works with model and build Robotics applications using Machine learning are included as chapters in this book.

Paperback. Etat : Brand New. 276 pages. 9.25x6.10x0.63 inches. In Stock.

paperback. Etat : Very Good.

Taschenbuch. Etat : Neu. Advances in Applications of Data-Driven Computing | Jagdish Chand Bansal (u. a.) | Taschenbuch | xii | Englisch | 2021 | Springer | EAN 9789813369184 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Paperback. Etat : Brand New. 196 pages. 9.25x6.10x0.46 inches. In Stock.

Etat : New. In.

Etat : New. In.

Taschenbuch. Etat : Neu. Neuware -This book aims to foster machine and deep learning approaches to data-driven applications, in which data governs the behaviour of applications. Applications of Artificial intelligence (AI)-based systems play a significant role in today¿s software industry. The sensors data from hardware-based systems making a mammoth database, increasing day by day. Recent advances in big data generation and management have created an avenue for decision-makers to utilize these huge volumes of data for different purposes and analyses. AI-based application developers have long utilized conventional machine learning techniques to design better user interfaces and vulnerability predictions. However, with the advancement of deep learning-based and neural-based networks and algorithms, researchers are able to explore and learn more about data and their exposed relationships or hidden features. This new trend of developing data-driven application systems seeks the adaptation of computational neural network algorithms and techniques in many application domains, including software systems, cyber security, human activity recognition, and behavioural modelling. As such, computational neural networks algorithms can be refined to address problems in data-driven applications. Original research and review works with model and build data-driven applications using computational algorithm are included as chapters in this book.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 196 pp. Englisch.

Etat : New. pp. XXIII, 252 1 Edition NO-PA16APR2015-KAP.

Etat : Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Machine learning has become one of the most prevalent topics in recent years. The application of machine learning we see today is a tip of the iceberg. The machine learning revolution has just started to roll out. It is becoming an integral part of all modern electronic devices. Applications in automation areas like automotive, security and surveillance, augmented reality, smart home, retail automation and healthcare are few of them. Robotics is also rising to dominate the automated world. The future applications of machine learning in the robotics area are still undiscovered to the common readers. We are, therefore, putting an effort to write this edited book on the future applications of machine learning on robotics where several applications have been included in separate chapters. The content of the book is technical. It has been tried to cover all possible application areas of Robotics using machine learning. This book will provide the future vision on the unexplored areas ofapplications of Robotics using machine learning. The ideas to be presented in this book are backed up by original research results. The chapter provided here in-depth look with all necessary theory and mathematical calculations. It will be perfect for laymen and developers as it will combine both advanced and introductory material to form an argument for what machine learning could achieve in the future. It will provide a vision on future areas of application and their approach in detail. Therefore, this book will be immensely beneficial for the academicians, researchers and industry project managers to develop their new project and thereby beneficial for mankind. Original research and review works with model and build Robotics applications using Machine learning are included as chapters in this book.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book aims to foster machine and deep learning approaches to data-driven applications, in which data governs the behaviour of applications. Applications of Artificial intelligence (AI)-based systems play a significant role in today's software industry. The sensors data from hardware-based systems making a mammoth database, increasing day by day. Recent advances in big data generation and management have created an avenue for decision-makers to utilize these huge volumes of data for different purposes and analyses. AI-based application developers have long utilized conventional machine learning techniques to design better user interfaces and vulnerability predictions. However, with the advancement of deep learning-based and neural-based networks and algorithms, researchers are able to explore and learn more about data and their exposed relationships or hidden features. This new trend of developing data-driven application systems seeks the adaptation of computational neural network algorithms and techniques in many application domains, including software systems, cyber security, human activity recognition, and behavioural modelling. As such, computational neural networks algorithms can be refined to address problems in data-driven applications. Original research and review works with model and build data-driven applications using computational algorithm are included as chapters in this book.