9798868817625 - Generative Ai in R: Transforming Data Science with Synthetic Data and Advanced Modeling Techniques by Singh, Akansha; Singh, Krishna Kant (19 results)

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Taschenbuch. Condition: Neu. Generative AI in R | Transforming Data Science with Synthetic Data and Advanced Modeling Techniques | Akansha Singh (u. a.) | Taschenbuch | xvi | Englisch | 2026 | Apress | EAN 9798868817625 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

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Paperback. Condition: new. Paperback. 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.Youll begin with an introduction to Generative AI principles and its significance in the current data-driven landscape. Youll 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 issuesconcerns 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. font-family: 'Times New Roman',serif; font-family: 'Times New Roman',serif; mso-fareast-language: EN-IN;"> and prepare for future directions and how new innovations can be applied in the R ecosystem This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 580 pp. Englisch.

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Paperback. Condition: new. Paperback. 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.Youll begin with an introduction to Generative AI principles and its significance in the current data-driven landscape. Youll 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 issuesconcerns 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. font-family: 'Times New Roman',serif; font-family: 'Times New Roman',serif; mso-fareast-language: EN-IN;"> and prepare for future directions and how new innovations can be applied in the R ecosystem This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condition: new. Paperback. 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.Youll begin with an introduction to Generative AI principles and its significance in the current data-driven landscape. Youll 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 issuesconcerns 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. font-family: 'Times New Roman',serif; font-family: 'Times New Roman',serif; mso-fareast-language: EN-IN;"> and prepare for future directions and how new innovations can be applied in the R ecosystem This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -1. Introduction to Generative AI and R.- 2. Setting up your R Environment for Generative AI.- 3. Fundamentals of Generative AI .- 4. Implementing Basic Generative Models in R.- 5. Generating Synthetic Data with R.- 6. Advanced Generative Models and Techniques.- 7. Generative AI for Predictive Modeling.- 8. Creative Applications of Generative AI in R.- 9. Ethical Considerations and Future Directions.- 10.Capstone Projects and Future Roadmap with R for Generative AI.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 596 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.