Machine Learning for Robotics Applications

Name: Machine Learning for Robotics Applications
Brand: Springer Verlag, Singapore
SKU: 9789811605970
Price: 69221 HUF
Availability: InStock

Szerző: Milan Simic, Ankush Ghosh

Nyelv:

Kötés: Kemény kötésű

Kiadó: Springer Verlag, Singapore

Elérhetőség: Beszállítói készleten

Küldés 10-13 napon belül

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Machine learning has become one of the most prevalent topics in recent years. The application of mac...

Információk a könyvről

Szerző

Milan Simic, Ankush Ghosh

Nyelv

Angol

Kötés

Könyv - Kemény kötésű

Kiadva

2021

oldal

180

EAN

9789811605970

ISBN

9811605971

Enbook ID

33614114

Kiadó

Springer Verlag, Singapore

Súly

442

Méretek

160 x 241 x 15

Teljes leírás

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 of applications 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.

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Machine Learning for Robotics Applications

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