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This book presents the idea that innovative ways of teaching and learning are very essential to retention and growth. Presented in 15 sections, the book starts with the common sense training on education and moves on to neural network operation. Throughout the book, the art of learning, associative, cognitive, and creative learning are stated and defined. Learning simplicity, information content as related to neural network learning are discussed. The author also discusses neural plasticity and adaptability in smarter neural networks.
If we know our human brain’s basic abilities and limitation then a better educational methods can be implemented.
Presents the idea that innovative ways of teaching and learning are very essential to retention and growth
Discusses major differences and constraints between neural network and computer
Presents the significances of learning simplicity and information content as related to neural network learning are included
Stresses the neural network learning capabilities and limitations and their role in developing more efficient learning techniques
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This book presents the idea that innovative ways of teaching and learning are very essential to retention and growth. Presented in 15 sections, the book starts with the common sense training on education and moves on to neural network operation. Throughout the book, the art of learning, associative, cognitive, and creative learning are stated and defined. Learning simplicity, information content as related to neural network learning are discussed. The author also discusses neural plasticity and adaptability in smarter neural networks.
If we know our human brain’s basic abilities and limitation then a better educational methods can be implemented.
Presents the idea that innovative ways of teaching and learning are very essential to retention and growth
Discusses major differences and constraints between neural network and computer
Presents the significances of learning simplicity and information content as related to neural network learning are included
Stresses the neural network learning capabilities and limitations and their role in developing more efficient learning techniques