Singh krishna kant (253 resultados)

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Condición: New. pp. 182 + [1].

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Condición: New. pp. vi + 296.

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Condición: New. pp. iv + [ii] + 282 1st Published.

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Condición: New. pp. iv + [ii] + 282 Epilogue.

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Paperback. Condición: New. First Edition. Leverage Generative AI within the R programming environment and prepare for future directions and how new innovations can be applied in the R ecosystem. This pioneering book is designed to bridge the gap between the advanced realms of Generative AI and the practical, statistical computing power of R.You'll begin with an introduction to Generative AI principles and its significance in the current data-driven landscape. You'll then dive into the practicalities of implementing generative models such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) in R. See how R, most known for its statistical analysis, can also be used for creative synthetic data, improving model robustness, and generating innovative insights from data. Additionally, this book addresses the demand for ethical AI by emphasizing the use of synthetic data to tackle privacy and data scarcity issues-concerns particularly relevant in healthcare, finance, and social research. We are at a pivotal moment in the evolution of AI and data science. With AI's growing importance, the book's focus on R makes advanced techniques more accessible, promoting ethical and innovative data science practice, preparing readers for upcoming trends.What You Will Learn Grasp the core concepts of Generative AI and its significance in the broader AI landscape.Implement various generative models in R, such as GANS and VAEs.Generate high-quality synthetic data.Apply advanced techniques for improving efficiency and effectiveness of models for different applications.Understand Gen AI ethical considerations.Who This Book Is For Data scientists and statisticians with intermediate R programming skills who want to expand into Generative AI for data analysis and problem-solving. AI enthusiasts and data analysts looking to apply Generative AI techniques in R to enhance their analytical capabilities.…

Contents Preface 1 Prologue 2 The Company of Women A Fictional Pornography in Disguise 3 The Blue Bedspread A Fiction of distorted relations 4 If you are Afraid of Heights Imposed Gloominess in self 5 The Romantics Conflict of a youth caught in His Cobweb of Unfulfilled ambition 6 The ground beneath her feet; Musical world of love and fantasy 7 Five point someone what not to do at IIT A Candid tale of three friends 8 One Night at the call centre A Tale of darkness due to endless struggle in life 9 The three mistakes of My Life A real story of Mission Obsession and sacrifice 10 Aravind Adiga?s The White Tiger Journey of a Man from Innocence to complexity 11 Epilogue BibliographyThe book throws lights on some of the important Indian novelists writing in English in the last two decades Novelists like Salman Rushdie Kushwant Singh Raj Kamal Jha Pankaj Mishra Chetan Bhagat and Aravind Adiga have shown extraordinary talent in handling of some modern thematic patterns and stylistic devices They artistically contribute in the journey of Indian writing in English which is now in the state of mainstream This book unfolds some of the features of their writings in modern perspectives with more help of their texts Jacket 184 pp.…

Paperback. Condición: New. First Edition. Leverage Generative AI within the R programming environment and prepare for future directions and how new innovations can be applied in the R ecosystem. This pioneering book is designed to bridge the gap between the advanced realms of Generative AI and the practical, statistical computing power of R.You'll begin with an introduction to Generative AI principles and its significance in the current data-driven landscape. You'll then dive into the practicalities of implementing generative models such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) in R. See how R, most known for its statistical analysis, can also be used for creative synthetic data, improving model robustness, and generating innovative insights from data. Additionally, this book addresses the demand for ethical AI by emphasizing the use of synthetic data to tackle privacy and data scarcity issues-concerns particularly relevant in healthcare, finance, and social research. We are at a pivotal moment in the evolution of AI and data science. With AI's growing importance, the book's focus on R makes advanced techniques more accessible, promoting ethical and innovative data science practice, preparing readers for upcoming trends.What You Will Learn Grasp the core concepts of Generative AI and its significance in the broader AI landscape.Implement various generative models in R, such as GANS and VAEs.Generate high-quality synthetic data.Apply advanced techniques for improving efficiency and effectiveness of models for different applications.Understand Gen AI ethical considerations.Who This Book Is For Data scientists and statisticians with intermediate R programming skills who want to expand into Generative AI for data analysis and problem-solving. AI enthusiasts and data analysts looking to apply Generative AI techniques in R to enhance their analytical capabilities.…