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Hands-On Neuroevolution with Python: Build high-performing artificial neural network architectures using neuroevolution-based algorithms
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Hands-On Neuroevolution with Python: Build high-performing artificial neural network architectures using neuroevolution-based algorithms
Equip yourself with the skills to apply neuroevolution-based algorithms to solve practical, real-world problems.
Hands-On Neuroevolution with Python: Build high-performing artificial neural network architectures using neuroevolution-based algorithms
Artikal br.: 24882960

Hands-On Neuroevolution with Python: Build high-performing artificial neural network architectures using neuroevolution-based algorithms

80% of respondents would recommend this to a friend

Artikal br.: 24882960

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Equip yourself with the skills to apply neuroevolution-based algorithms to solve practical, real-world problems.
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What Stands Out

Neuroevolution Techniques
Utilizes advanced neuroevolution algorithms, allowing users to create highly adaptable neural networks, elevating performance beyond traditional methods and addressing optimization challenges effectively.
Python Integration
Seamless integration with Python enhances accessibility for developers, fostering innovative implementations while leveraging existing libraries and tools within the Python ecosystem for machine learning.
Hands-On Approach
Encourages practical learning through hands-on projects, enabling users to apply theoretical concepts in real-world scenarios, thus solidifying understanding and enhancing skills in neural network design.

Detalji o proizvodu

Discover the power of neuroevolution-based algorithms for building artificial neural networks. Buy the paperback book on Ubuy Bosnia and Herzegovina.
Publisher Packt Publishing
Publication date December 24, 2019
Language English
Print length 368 pages
ISBN-10 183882491X
ISBN-13 978-1838824914
Item Weight 1.48 pounds (670 grams)
Dimensions 7.5 x 0.83 x 9.25 inches (19.1 x 2.1 x 23.5 cm)

Who Should Buy?

Suitable For
  • AI Developers

    Ideal for developers looking to enhance their AI models using neuroevolution techniques for performance optimization.

  • Machine Learning Students

    Great for students who want to understand and apply advanced neural network concepts and neuroevolution strategies.

  • Research Enthusiasts

    Perfect for researchers focusing on evolutionary algorithms and their application in artificial intelligence methodologies.

Not Suitable For
  • Beginners

    Not suitable for those new to programming or machine learning, as it requires prior knowledge and experience.

OPIS PROIZVODA

Hands-On Neuroevolution with Python: Build high-performing artificial neural network architectures using neuroevolution-based algorithms

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  • Pitanje: Kako kupovati Hands-On Neuroevolution with Python: Build online od Ubuya?

    Odgovor: Lako je kupovati Hands-On Neuroevolution with Python: Build online od Ubuya.. Vi samo trebate potražiti proizvod, odabrati način dostave prilikom odjavljivanja i dostaviti ga na vašu lokaciju.
  • Pitanje: Je li Hands-On Neuroevolution with Python: Build dostupan za online kupovinu u Bosnia and Herzegovina?

    Odgovor: Da, u Ubuy Bosnia and Herzegovina ovaj proizvod je dostupan za kupovinu po razumnoj cijeni.. Hands-On Neuroevolution with Python: Build nije dostupan lokalno, ali možete nam povjeriti naše usluge ekspresne dostave.
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Pros

  • Engaging hands-on approach
  • Covers neuroevolution algorithms
  • Accessible for beginners
  • Practical project examples
  • Well-structured content

Cons

  • Some concepts require deeper understanding.

Product Price History

Važna informacija

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Karakteristike i prednosti

  • Learn essential neuroevolution concepts and methods with Python.
  • Implement popular algorithms like NEAT, HyperNEAT, and ES-HyperNEAT.
  • Gain hands-on experience with advanced Python libraries.
  • Explore practical applications in games, robotics, and simulations.
  • Improve the performance of existing neural networks with neuroevolution strategies.
  • Develop agents that autonomously play games using deep neuroevolution.

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