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Stochastic Processes and Their Applications in Artificial Intelligence

Om Stochastic Processes and Their Applications in Artificial Intelligence

Stochastic processes have a wide range of applications ranging from image processing, neuroscience, bioinformatics, financial management, and statistics. Mathematical, physical, and engineering systems use stochastic processes for modeling and reasoning phenomena. While comparing AI-stochastic systems with other counterpart systems, we are able to understand their significance, thereby applying new techniques to obtain new real-time results and solutions. Stochastic Processes and Their Applications in Artificial Intelligence opens doors for artificial intelligence experts to use stochastic processes as an effective tool in real-world problems in computational biology, speech recognition, natural language processing, and reinforcement learning. Covering key topics such as social media, big data, and artificial intelligence models, this reference work is ideal for mathematicians, industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.

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  • Språk:
  • Engelska
  • ISBN:
  • 9781668476802
  • Format:
  • Häftad
  • Sidor:
  • 244
  • Utgiven:
  • 10. juli 2023
  • Mått:
  • 178x13x254 mm.
  • Vikt:
  • 467 g.
  Fri leverans
Leveranstid: 2-4 veckor
Förväntad leverans: 18. december 2024
Förlängd ångerrätt till 31. januari 2025

Beskrivning av Stochastic Processes and Their Applications in Artificial Intelligence

Stochastic processes have a wide range of applications ranging from image processing, neuroscience, bioinformatics, financial management, and statistics. Mathematical, physical, and engineering systems use stochastic processes for modeling and reasoning phenomena. While comparing AI-stochastic systems with other counterpart systems, we are able to understand their significance, thereby applying new techniques to obtain new real-time results and solutions. Stochastic Processes and Their Applications in Artificial Intelligence opens doors for artificial intelligence experts to use stochastic processes as an effective tool in real-world problems in computational biology, speech recognition, natural language processing, and reinforcement learning. Covering key topics such as social media, big data, and artificial intelligence models, this reference work is ideal for mathematicians, industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.

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