neural network
Computational Cognitive Science.pdf
Human learning and reasoning is founded on multiple knowledge representations with different kinds of structures, such as trees, chains, dominance hierarchies, neighborhood graphs, and directed networks. This class uses probabilistic inference methods from machine learning and Bayesian statistics, operating over different kinds of structured representational systems, to explain how people’s domain knowledge can support a wide range of learning and reasoning tasks, and how these knowledge structures may themselves be learned from experience.
The Scientist and Engineer’s Guide to Digital Signal Processing.pdf
The Scientist and Engineers Guide to Digital Signal Processing.pdf was written for a wide range of fields: physics, bioengineering, geology, oceanography, mechanical and electrical engineering..
Artificial Intelligence Course Material.pdf
41 Lessons in 13 modules of Artificial Intelligence ebook, pictures and words work together to explain as concise as possible everything about Artificial Intelligence, you can find logic, fuzzy, agent, single agent search and more
Practical Artificial Intelligence Programming in Java.pdf
Practical Artificial Intelligence Programming in Java.pdf, written by Mark Watson is written either for proffesional or hobbyist who want to learn Practical Artificial Intelligence in Java.
An Introduction to Intelligent and Autonomous Control.pdf
An introduction to the field of intelligent control with a broad treatment of topics by several authors (including hierarchical/ distributed intelligent control, fuzzy control, expert control, neural networks, planning systems, and applications).
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