Recognizing the vast potential in analyzing big data through machine learning (ML) and artificial intelligence (AI) technologies, companies are acknowledging these technologies as essential for maintaining relevance. A prevailing trend is emerging toward the adoption of distributed open‑source computing for storing big data assets and performing advanced ML/AI analytics to predict future trends and risks for businesses. This book offers readers an overview of the essentials of big data and ML/AI, while acknowledging that the field is extensive and evolving. In addition to focusing on theory, this book shares real‑life experiences building AI and big data analytics systems of value to practitioners.
Informed by the authors’ many years of teaching ML and AI and working on predictive data analytics/AI projects, this book is suitable for use by graduates, professionals, and researchers within the field of data science and engineers and scientists interested in learning more about these essential technologies.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Satish Mahadevan Srinivasan is an Associate Professor of Information Science at Pennsylvania State University, Great Valley. He teaches courses related to database design, data mining, data collection and cleaning, data visualization, computer, network and web securities, network analytics and business process management.
Raghvinder S. Sangwan is a Professor of Software Engineering at Pennsylvania State University with expertise in analysis, design, and development of large‑scale software‑intensive systems, and the use of AI engineering to design and develop intelligent systems that are safe, secure, and trustworthy.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. Codice articolo 408745051
Quantità: 3 disponibili
Da: Biblios, Frankfurt am main, HESSE, Germania
Condizione: New. Codice articolo 18405490574
Quantità: 3 disponibili
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
Paperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days. Codice articolo B9781032829852
Quantità: Più di 20 disponibili
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. Codice articolo 26405490564
Quantità: 3 disponibili
Da: moluna, Greven, Germania
Condizione: New. Satish Mahadevan Srinivasan is an Associate Professor of Information Science at Pennsylvania State University, Great Valley. He teaches courses related to database design, data mining, data collection and cleaning, data visualization, co. Codice articolo 2839077631
Quantità: Più di 20 disponibili
Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. Neuware - Recognizing the vast potential in analyzing big data through machine learning (ML) and artificial intelligence (AI) technologies, companies are acknowledging these technologies as essential for maintaining relevance. A prevailing trend is emerging toward the adoption of distributed open¿source computing for storing big data assets and performing advanced ML/AI analytics to predict future trends and risks for businesses. This book offers readers an overview of the essentials of big data and ML/AI, while acknowledging that the field is extensive and evolving. In addition to focusing on theory, this book shares real¿life experiences building AI and big data analytics systems of value to practitioners. - Features practical case studies on building big data and AI models for large¿scale enterprise solutions - Discusses the use of design patterns for architecting AI that are safe, secure, and testable - Covers an array of concepts, including deep big data analytics, natural language processing, transformer architecture, and evolution of ChatGPT, swarm intelligence, and genetic programming Informed by the authors' many years of teaching ML and AI and working on predictive data analytics/AI projects, this book is suitable for use by graduates, professionals, and researchers within the field of data science and engineers and scientists interested in learning more about these essential technologies. Codice articolo 9781032829852
Quantità: 2 disponibili