Shankar Ananda (12 results)

Condition: New.

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Taschenbuch. Condition: Neu. Neuware - Dancing with Joy is an inspiring memoir by Ananda Shankar Jayant, one of India's most celebrated classical dancers, whose life unfolds at the intersection of art, intellect, and public service. Her journey is one of discipline, grace, resilience, and quiet courage.At the heart of this remarkable story is her encounter with cancer-met not as an ending, but as another rhythm to be understood, challenged, and ultimately mastered. 'Cancer is a mind game,' she writes, 'and dance-my core strength-taught me to ride both the crab and my mind.'Rich with insight, wisdom, and deeply personal reflections, Dancing with Joy is a celebration of the human spirit's ability to rise above adversity. Through triumphs, setbacks, and moments of profound self-discovery, Ananda inspires readers to recognize and nurture their unique gifts while embracing life with purpose and gratitude.More than a memoir of survival, this is a story of transformation, resilience, and the conscious choice to find joy again and again. It offers hope and strength to anyone facing uncertainty, self-doubt, illness, or life's unexpected turns.…

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Condition: New.

Condition: New.

Paperback. Condition: new. Paperback. Dancing with Joy is an inspiring memoir by Ananda Shankar Jayant, one of India's most celebrated classical dancers, whose life unfolds at the intersection of art, intellect, and public service. Her journey is one of discipline, grace, resilience, and quiet courage.At the heart of this remarkable story is her encounter with cancer-met not as an ending, but as another rhythm to be understood, challenged, and ultimately mastered. "Cancer is a mind game," she writes, "and dance-my core strength-taught me to ride both the crab and my mind."Rich with insight, wisdom, and deeply personal reflections, Dancing with Joy is a celebration of the human spirit's ability to rise above adversity. Through triumphs, setbacks, and moments of profound self-discovery, Ananda inspires readers to recognize and nurture their unique gifts while embracing life with purpose and gratitude.More than a memoir of survival, this is a story of transformation, resilience, and the conscious choice to find joy again and again. It offers hope and strength to anyone facing uncertainty, self-doubt, illness, or life's unexpected turns. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Condition: new. Hardcover. This Reprint presents a collection of cutting-edge research and review articles focusing on the integration of machine learning and deep learning theories for intelligent fault diagnosis in industrial and engineering systems. With the rapid advancement of computational intelligence, data-driven fault diagnosis has become a cornerstone of modern Prognostics and Health Management (PHM), enabling early detection, prediction, and mitigation of system failures. The contributions in this Reprint highlight innovative applications of artificial neural networks, convolutional and recurrent neural architectures, transfer learning, and hybrid intelligent systems for diagnosing faults in rotating machinery, robotic systems, power plants, and manufacturing processes. In addition, the included studies explore explainable AI models, data augmentation, and sensor fusion methods that enhance model interpretability and robustness under real-world operating conditions. By bringing together theoretical insights and practical implementations, this Reprint aims to serve as a valuable reference for researchers, engineers, and practitioners engaged in machine learning-based condition monitoring and intelligent fault diagnosis. It reflects recent trends shaping the future of autonomous and resilient industrial systems within the framework of Industry 4.0. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This Reprint presents a collection of cutting-edge research and review articles focusing on the integration of machine learning and deep learning theories for intelligent fault diagnosis in industrial and engineering systems. With the rapid advancement of computational intelligence, data-driven fault diagnosis has become a cornerstone of modern Prognostics and Health Management (PHM), enabling early detection, prediction, and mitigation of system failures. The contributions in this Reprint highlight innovative applications of artificial neural networks, convolutional and recurrent neural architectures, transfer learning, and hybrid intelligent systems for diagnosing faults in rotating machinery, robotic systems, power plants, and manufacturing processes. In addition, the included studies explore explainable AI models, data augmentation, and sensor fusion methods that enhance model interpretability and robustness under real-world operating conditions. By bringing together theoretical insights and practical implementations, this Reprint aims to serve as a valuable reference for researchers, engineers, and practitioners engaged in machine learning-based condition monitoring and intelligent fault diagnosis. It reflects recent trends shaping the future of autonomous and resilient industrial systems within the framework of Industry 4.0.…

Buch. Condition: Neu. Recent Advances in Machine learning and Deep Learning Theories | Towards Intelligent Fault Diagnosis | Buch | Englisch | 2026 | MDPI AG | EAN 9783725859511 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …