{"product_id":"9789355854476","title":"Neural Networks  and Deep Learning  for BE Anna University R21CBCS (V, VI, VII, VIII(Vertical I\/VI\/VII - CSE\/IT\/CS\u0026BS, Vertical III - CS\u0026BS, Vertical VI - AI\u0026DS, Vertical  VII - CS\u0026BS , VI - ECE\/Open Elective-I - CCS355)","description":"\u003cp\u003eSyllabus Neural Networks and Deep Learning - [CCS355] UNIT I\tINTRODUCTION Neural Networks-Application Scope of Neural Networks - Artificial Neural Network : An Introduction - Evolution of Neural Networks - Basic Models of Artificial Neural Network- Important Terminologies of ANNs - Supervised Learning Network. (Chapter - 1) UNIT II\tASSOCIATIVE MEMORY AND UNSUPERVISED  \t\tLEARNING NETWORKS Training Algorithms for Pattern Association-Autoassociative Memory Network-Heteroassociative Memory Network-Bidirectional Associative Memory (BAM) - Hopfield Networks - Iterative Autoassociative Memory Networks - Temporal Associative Memory Network-Fixed Weight Competitive Nets-Kohonen Self - Organizing Feature Maps-Learning Vector Quantization-Counter propagation Networks-Adaptive Resonance Theory Network. (Chapter - 2) UNIT III\tTHIRD-GENERATION NEURAL NETWORKS Spiking Neural Networks - Convolutional Neural Networks-Deep Learning Neural Networks-Extreme Learning Machine Model - Convolutional Neural Networks : The Convolution Operation - Motivation - Pooling - Variants of the basic Convolution Function - Structured Outputs - Data Types - Efficient Convolution Algorithms - Neuroscientific Basis - Applications : Computer Vision, Image Generation, Image Compression. (Chapter - 3) UNIT IV\tDEEP FEEDFORWARD NETWORKS History of Deep Learning - A Probabilistic Theory of Deep Learning - Gradient Learning - Chain Rule and Backpropagation - Regularization : Dataset Augmentation - Noise Robustness - Early Stopping, Bagging and Dropout - batch normalization- VC Dimension and Neural Nets.  (Chapter - 4) UNIT V\tRECURRENT NEURAL NETWORKS Recurrent Neural Networks : Introduction - Recursive Neural Networks - Bidirectional RNNs - Deep Recurrent Networks - Applications : Image Generation, Image Compression, Natural Language Processing. Complete Auto encoder, Regularized Autoencoder, Stochastic Encoders and Decoders, Contractive Encoders. (Chapter - 5)\u003c\/p\u003e","brand":"Technical Publications","offers":[{"title":"Default Title","offer_id":47489134199076,"sku":"9789355854476","price":220.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0671\/3661\/8788\/files\/9789355854476_1.jpg?v=1699012015","url":"https:\/\/bookstation.in\/mr\/products\/9789355854476","provider":"BookStation","version":"1.0","type":"link"}