Prasanth Aruchamy (72 results)
Generative Ai and Llms : Natural Language Processing and Generative Adversarial Networks
Balasubramaniam, S. (EDT); Kadry, Seifedine (EDT); Prasanth, Aruchamy (EDT); Kumar Dhanaraj, Rajesh (EDT)
- Hardcover
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Generative Ai and Llms : Natural Language Processing and Generative Adversarial Networks
Balasubramaniam, S. (EDT); Kadry, Seifedine (EDT); Prasanth, Aruchamy (EDT); Kumar Dhanaraj, Rajesh (EDT)
- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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Generative Ai and Llms : Natural Language Processing and Generative Adversarial Networks
Balasubramaniam, S. (EDT); Kadry, Seifedine (EDT); Prasanth, Aruchamy (EDT); Kumar Dhanaraj, Rajesh (EDT)
- Hardcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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- Hardcover
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- Softcover
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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Generative Ai and Llms : Natural Language Processing and Generative Adversarial Networks
Balasubramaniam, S. (EDT); Kadry, Seifedine (EDT); Prasanth, Aruchamy (EDT); Kumar Dhanaraj, Rajesh (EDT)
- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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- Hardcover
- First Edition
Seller: Rarewaves USA, OSWEGO, IL, U.S.A.Rarewaves USA
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Hardback. Condition: New. 1st. Generative artificial intelligence (GAI) and large language models (LLM) are machine learning algorithms that operate in an unsupervised or semi-supervised manner. These algorithms leverage pre-existing content, such as text, photos, audio, video, and code, to generate novel content. The primary ob…jective is to produce authentic and novel material. In addition, there exists an absence of constraints on the quantity of novel material that they are capable of generating. New material can be generated through the utilization of Application Programming Interfaces (APIs) or natural language interfaces, such as the ChatGPT developed by Open AI and Bard developed by Google. The field of generative artificial intelligence (AI) stands out due to its unique characteristic of undergoing development and maturation in a highly transparent manner, with its progress being observed by the public at large. The current era of artificial intelligence is being influenced by the imperative to effectively utilise its capabilities in order to enhance corporate operations. Specifically, the use of large language model (LLM) capabilities, which fall under the category of Generative AI, holds the potential to redefine the limits of innovation and productivity. However, as firms strive to include new technologies, there is a potential for compromising data privacy, long-term competitiveness, and environmental sustainability. This book delves into the exploration of generative artificial intelligence (GAI) and LLM. It examines the historical and evolutionary development of generative AI models, as well as the challenges and issues that have emerged from these models and LLM. This book also discusses the necessity of generative AI-based systems and explores the various training methods that have been developed for generative AI models, including LLM pretraining, LLM fine-tuning, and reinforcement learning from human feedback. Additionally, it explores the potential use cases, applications, and ethical considerations associated with these models. This book concludes by discussing future directions in generative AI and presenting various case studies that highlight the applications of generative AI and LLM.
Climate Smart Agriculture
Velu, Anitha (EDT); Prasanth, A. (EDT); Ramamoorthy, Raghu (EDT); Dhanaraj, Rajesh Kumar (EDT); Kadry, Seifedine (EDT)
- Hardcover
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- Hardcover
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Hardcover. Condition: new. Hardcover. Transform the future of sustainable farming with this guide to mastering deep reinforcement learning architectures and algorithms that turn complex environmental data into precise, high-yield decisions for climate-smart agriculture. It conveys the importance of deep reinforcement learning an…d its technological advancements across climate-smart agriculture applications, addresses challenges related to privacy, security, and scalability of climatic and agricultural data, and explains reinforcement learning from AI and optimal control perspectives. The book explores advanced solutions such as meta learning, hierarchical learning, multi-agent learning, and imitation learning, emphasizing modern frameworks, algorithms, tools, and decision-making systems that support farmers through intelligent, data-driven applications. A machine learning method called reinforcement learning trains computers to make decisions that produce optimal outcomes by learning through trial and error. Applicable across robotics, autonomous vehicles, healthcare, finance, and agriculture, reinforcement learning plays a critical role in modern intelligent systems. This book provides a detailed analysis of climate-smart agriculture, examining farmers challenges, current technology-enabled systems, and deep reinforcement learning frameworks, algorithms, and architectures. It also addresses data privacy, security, and scalability issues in applications such as yield prediction, crop management, disease prediction, soil health monitoring, precision agriculture, and environmental monitoring. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Seller: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, GermanyRheinberg-Buch Andreas Meier eK
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Buch. Condition: Neu. Neuware - Generative artificial intelligence (GAI) and large language models (LLM) are machine learning algorithms that operate in an unsupervised or semi-supervised manner. These algorithms leverage pre-existing content, such as text, photos, audio, video, and code, to generate novel content. The primary o…bjective is to produce authentic and novel material. In addition, there exists an absence of constraints on the quantity of novel material that they are capable of generating. New material can be generated through the utilization of Application Programming Interfaces (APIs) or natural language interfaces, such as the ChatGPT developed by Open AI and Bard developed by Google. The field of generative artificial intelligence (AI) stands out due to its unique characteristic of undergoing development and maturation in a highly transparent manner, with its progress being observed by the public at large. The current era of artificial intelligence is being influenced by the imperative to effectively utilise its capabilities in order to enhance corporate operations. Specifically, the use of large language model (LLM) capabilities, which fall under the category of Generative AI, holds the potential to redefine the limits of innovation and productivity. However, as firms strive to include new technologies, there is a potential for compromising data privacy, long-term competitiveness, and environmental sustainability. This book delves into the exploration of generative artificial intelligence (GAI) and LLM. It examines the historical and evolutionary development of generative AI models, as well as the challenges and issues that have emerged from these models and LLM. This book also discusses the necessity of generative AI-based systems and explores the various training methods that have been developed for generative AI models, including LLM pretraining, LLM fine-tuning, and reinforcement learning from human feedback. Additionally, it explores the potential use cases, applications, and ethical considerations associated with these models. This book concludes by discussing future directions in generative AI and presenting various case studies that highlight the applications of generative AI and LLM. Englisch.
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- Hardcover
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Buch. Condition: Neu. Neuware - Generative artificial intelligence (GAI) and large language models (LLM) are machine learning algorithms that operate in an unsupervised or semi-supervised manner. These algorithms leverage pre-existing content, such as text, photos, audio, video, and code, to generate novel content. The primary o…bjective is to produce authentic and novel material. In addition, there exists an absence of constraints on the quantity of novel material that they are capable of generating. New material can be generated through the utilization of Application Programming Interfaces (APIs) or natural language interfaces, such as the ChatGPT developed by Open AI and Bard developed by Google. The field of generative artificial intelligence (AI) stands out due to its unique characteristic of undergoing development and maturation in a highly transparent manner, with its progress being observed by the public at large. The current era of artificial intelligence is being influenced by the imperative to effectively utilise its capabilities in order to enhance corporate operations. Specifically, the use of large language model (LLM) capabilities, which fall under the category of Generative AI, holds the potential to redefine the limits of innovation and productivity. However, as firms strive to include new technologies, there is a potential for compromising data privacy, long-term competitiveness, and environmental sustainability. This book delves into the exploration of generative artificial intelligence (GAI) and LLM. It examines the historical and evolutionary development of generative AI models, as well as the challenges and issues that have emerged from these models and LLM. This book also discusses the necessity of generative AI-based systems and explores the various training methods that have been developed for generative AI models, including LLM pretraining, LLM fine-tuning, and reinforcement learning from human feedback. Additionally, it explores the potential use cases, applications, and ethical considerations associated with these models. This book concludes by discussing future directions in generative AI and presenting various case studies that highlight the applications of generative AI and LLM. Englisch.
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- Hardcover
Seller: Wegmann1855, Zwiesel, GermanyWegmann1855
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Buch. Condition: Neu. Neuware -Generative artificial intelligence (GAI) and large language models (LLM) are machine learning algorithms that operate in an unsupervised or semi-supervised manner. These algorithms leverage pre-existing content, such as text, photos, audio, video, and code, to generate novel content. The primary ob…jective is to produce authentic and novel material. In addition, there exists an absence of constraints on the quantity of novel material that they are capable of generating. New material can be generated through the utilization of Application Programming Interfaces (APIs) or natural language interfaces, such as the ChatGPT developed by Open AI and Bard developed by Google. The field of generative artificial intelligence (AI) stands out due to its unique characteristic of undergoing development and maturation in a highly transparent manner, with its progress being observed by the public at large. The current era of artificial intelligence is being influenced by the imperative to effectively utilise its capabilities in order to enhance corporate operations. Specifically, the use of large language model (LLM) capabilities, which fall under the category of Generative AI, holds the potential to redefine the limits of innovation and productivity. However, as firms strive to include new technologies, there is a potential for compromising data privacy, long-term competitiveness, and environmental sustainability. This book delves into the exploration of generative artificial intelligence (GAI) and LLM. It examines the historical and evolutionary development of generative AI models, as well as the challenges and issues that have emerged from these models and LLM. This book also discusses the necessity of generative AI-based systems and explores the various training methods that have been developed for generative AI models, including LLM pretraining, LLM fine-tuning, and reinforcement learning from human feedback. Additionally, it explores the potential use cases, applications, and ethical considerations associated with these models. This book concludes by discussing future directions in generative AI and presenting various case studies that highlight the applications of generative AI and LLM.
- Softcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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Climate Smart Agriculture
Velu, Anitha (EDT); Prasanth, A. (EDT); Ramamoorthy, Raghu (EDT); Dhanaraj, Rajesh Kumar (EDT); Kadry, Seifedine (EDT)
- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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- Hardcover
Seller: moluna, Greven, Germanymoluna
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Condition: New. S. Balasubramaniam, S. Kadry, Norway A. Prasanth, R. Dhanaraj, India. Generative artificial intelligence (GAI) and large language models (LLM) are machine learning algorithms.
Climate Smart Agriculture
Velu, Anitha (EDT); Prasanth, A. (EDT); Ramamoorthy, Raghu (EDT); Dhanaraj, Rajesh Kumar (EDT); Kadry, Seifedine (EDT)
- Hardcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Condition: As New. Unread book in perfect condition.
- Softcover
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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- Softcover
Seller: THE SAINT BOOKSTORE, Southport, United KingdomTHE SAINT BOOKSTORE
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Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.
- Softcover
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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- Hardcover
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HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Seller: preigu, Osnabrück, Germanypreigu
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Buch. Condition: Neu. Generative AI and LLMs | Natural Language Processing and Generative Adversarial Networks | S. Balasubramaniam (u. a.) | Buch | XIV | Englisch | 2024 | Walter de Gruyter | EAN 9783111424637 | Verantwortliche Person für die EU: Walter de Gruyter GmbH, De Gruyter GmbH, Genthiner Str. 13, 10785 Berlin, products…afety[at]degruyterbrill[dot]com | Anbieter: preigu.
- Hardcover
Seller: Brook Bookstore On Demand, Napoli, NA, ItalyBrook Bookstore On Demand
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- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Hardcover. Condition: Brand New. 289 pages. 9.44x6.69x9.61 inches. In Stock.
Climate Smart Agriculture
Velu, Anitha (EDT); Prasanth, A. (EDT); Ramamoorthy, Raghu (EDT); Dhanaraj, Rajesh Kumar (EDT); Kadry, Seifedine (EDT)
- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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- Softcover
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Green Flexible Electronics for Sustainable Healthcare
Velu, Anitha (EDT); Aruchamy, Prasanth (EDT); Ramamoorthy, Raghu (EDT); Dhanaraj, Rajesh Kumar (EDT); S M, Manasa (EDT)
- Softcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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- First Edition
Seller: Rarewaves USA United, OSWEGO, IL, U.S.A.Rarewaves USA United
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Hardback. Condition: New. 1st. Generative artificial intelligence (GAI) and large language models (LLM) are machine learning algorithms that operate in an unsupervised or semi-supervised manner. These algorithms leverage pre-existing content, such as text, photos, audio, video, and code, to generate novel content. The primary ob…jective is to produce authentic and novel material. In addition, there exists an absence of constraints on the quantity of novel material that they are capable of generating. New material can be generated through the utilization of Application Programming Interfaces (APIs) or natural language interfaces, such as the ChatGPT developed by Open AI and Bard developed by Google. The field of generative artificial intelligence (AI) stands out due to its unique characteristic of undergoing development and maturation in a highly transparent manner, with its progress being observed by the public at large. The current era of artificial intelligence is being influenced by the imperative to effectively utilise its capabilities in order to enhance corporate operations. Specifically, the use of large language model (LLM) capabilities, which fall under the category of Generative AI, holds the potential to redefine the limits of innovation and productivity. However, as firms strive to include new technologies, there is a potential for compromising data privacy, long-term competitiveness, and environmental sustainability. This book delves into the exploration of generative artificial intelligence (GAI) and LLM. It examines the historical and evolutionary development of generative AI models, as well as the challenges and issues that have emerged from these models and LLM. This book also discusses the necessity of generative AI-based systems and explores the various training methods that have been developed for generative AI models, including LLM pretraining, LLM fine-tuning, and reinforcement learning from human feedback. Additionally, it explores the potential use cases, applications, and ethical considerations associated with these models. This book concludes by discussing future directions in generative AI and presenting various case studies that highlight the applications of generative AI and LLM.
