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How We Did It: 100 entrepreneurs share the story of their struggles and life experiences
Published by CreateSpace Independent Publishing Platform, 2014
ISBN 10: 149759975X ISBN 13: 9781497599758
Language: English
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Mysterious Temples of India
Published by ? Taxmann Publications, 2025
ISBN 10: 9364553586 ISBN 13: 9789364553582
Language: English
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Mysterious Temples of India
Published by Taxmann Publications Pvt Ltd, IN, 2025
ISBN 10: 9364553586 ISBN 13: 9789364553582
Language: English
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Beauty in the Uncertain Mirroring Physicians & Surgeons
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Mysterious Temples of India
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Mysterious Temples Of India
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Mysterious Temples Of India
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Add to basketPaperback. Condition: Brand New. 256 pages. 8.66x5.51x0.94 inches. In Stock.
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How We Did It: 100 entrepreneurs share the story of their struggles and life experiences
Published by CreateSpace Independent Publishing Platform, 2014
ISBN 10: 149759975X ISBN 13: 9781497599758
Language: English
Condition: New. Print on Demand.
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Add to basketPaperback. Condition: new. Paperback. Ananya Anand Srinivasan is a Year 4 Undergraduate Medical Student at Sri Ramachandra Medical College, Chennai, with a strong passion for both medicine and literature. Since the age of 8, she has shown a keen interest in literature and poetry, which led her to publish four books, including two on culture and heritage. Her first book, Ananya's Creations for Jubilant Juniors, was released in 2013 by Miss Arya Rajam, author of Blood, Sweat and Tears. Ananya has been actively involved in club activities, serving as the Organizing Head of the English Literary Club at SRIHER. She also co-authored the ISO-certified book Sway of the Little Pen Tip. Ananya's dedication to medicine is evident in her enthusiasm for learning and her belief that making and correcting mistakes is an essential part of the journey. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Condition: As New. Unread book in perfect condition.
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Handbook on Federated Learning (Paperback)
Published by Taylor & Francis Ltd, London, 2025
ISBN 10: 1032471638 ISBN 13: 9781032471631
Language: English
Paperback. Condition: new. Paperback. Mobile, wearable, and self-driving telephones are just a few examples of modern distributed networks that generate enormous amount of information every day. Due to the growing computing capacity of these devices as well as concerns over the transfer of private information, it has become important to process the part of the data locally by moving the learning methods and computing to the border of devices. Federated learning has developed as a model of education in these situations. Federated learning (FL) is an expert form of decentralized machine learning (ML). It is essential in areas like privacy, large-scale machine education and distribution. It is also based on the current stage of ICT and new hardware technology and is the next generation of artificial intelligence (AI). In FL, central ML model is built with all the data available in a centralised environment in the traditional machine learning. It works without problems when the predictions can be served by a central server. Users require fast responses in mobile computing, but the model processing happens at the sight of the server, thus taking too long. The model can be placed in the end-user device, but continuous learning is a challenge to overcome, as models are programmed in a complete dataset and the end-user device lacks access to the entire data package. Another challenge with traditional machine learning is that user data is aggregated at a central location where it violates local privacy policies laws and make the data more vulnerable to data violation. This book provides a comprehensive approach in federated learning for various aspects. Federated learning is a Distributed Machine Learning model that has been used in many applications today. Most edge devices can execute models with local dataset since their computation power is unutilized. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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