Jin - Data-Driven Evolutionary Optimization Integrating Evolutionary - X555z
A must-have for anyone interested in the intersection of evolutionary computation, machine learning, and data science.
Jin - Data-Driven Evolutionary Optimization Integrating Evolutionary - X555z

Nº de artículo: 138700970

Jin - Data-Driven Evolutionary Optimization Integrating Evolutionary - X555z

Nº de artículo: 138700970

NIO 10320

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A must-have for anyone interested in the intersection of evolutionary computation, machine learning, and data science.
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What Stands Out

Data-Driven Insights
Utilizing advanced data analytics, Jin delivers actionable insights that refine optimization processes, increasing efficiency and effectiveness beyond traditional methods.
Evolutionary Algorithms
Jin's integration of evolutionary algorithms allows for adaptive problem-solving, making it highly effective for complex challenges in various domains, standing out from competitors.
User-Friendly Interface
Designed with usability in mind, Jin ensures that both novices and experts can navigate its features easily, promoting adoption and maximizing user productivity.

Detalles de producto

Shop Jin - Data-Driven Evolutionary Optimization Integrating Evolutionary - X555z online at a best price in Nicaragua. 387006385121
Fiction/Non-FictionNon-Fiction
Genre/SubjectCOMPUTERS / Data Science / General
BrandNA
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Release TitleData-Driven Evolutionary Optimization Integrating Evolutionary
Record GradingNew
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Film/TV TitleData-Driven Evolutionary Optimization Integrating Evolutionary
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Binding TypeHardcover
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ISBN9783030746391
Country of OriginUnited States
Item Weight1 lbs (450 grams)

Who Should Buy?

Suitable For
  • Data Scientists

    Ideal for data scientists looking to implement advanced evolutionary algorithms for optimizing complex datasets and models.

  • Research Institutions

    Perfect for research institutions engaged in computational studies that require innovative optimization methodologies for their projects.

  • AI Developers

    Useful for AI developers seeking efficient ways to enhance machine learning models through evolutionary optimization techniques.

Not Suitable For
  • Casual Users

    Not suitable for casual users who lack the technical expertise to utilize advanced data-driven optimization tools effectively.

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Preguntas y respuestas de los clientes

  • Pregunta: What is the condition of the book?

    Respuesta: The book is in new condition.
  • Pregunta: What topics are covered in the book?

    Respuesta: The book integrates evolutionary computation, machine learning, and data science.
  • Pregunta: Can I choose a specific edition?

    Respuesta: Please contact us to verify if a specific edition is available.

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