Adaptive Neural Network Systems For Evolving AI Knowledge Engineering Approach A Practical Hands On Guide To Build Smart Self Improving Models For Developers And Data Science Pros No Fluff

Adaptive Neural Networks for Evolving Knowledge Engineering
✔️ 2nd edition, 473 illustrated pages, English, released 2007

The second edition presents generic computational models and techniques for developing evolving, adaptive modeling systems, with new trends including computational neuro-genetic modeling and quantum information processing related to evolving systems. New applications such as autonomous robots, adaptive artificial life systems and adaptive decision support systems are also covered.

✅ Author: Nikola K. Kasabov
✅ Edition: 2nd, illustrated, 473 pages, English
✅ Topics: generic computational models for evolving adaptive systems
✅ New topics: computational neuro-genetic modeling and quantum information processing
✅ Applications: autonomous robots, adaptive artificial life systems, adaptive decision support
✅ Release date: 15-08-2007

💡 What is an adaptive neural network guide best used for in AI development?
Handy for developers and data scientists seeking practical methods for building evolving, self-improving models
- Practical, hands-on methods for building evolving, self-improving models
- Covers computational neuro-genetic modeling and quantum information processing
- Includes applications like autonomous robots, adaptive artificial life, and adaptive decision support