Introduction to deep learning : from logical calculus to artificial intelligence /
006.312
Skansi, Sandro,
Introduction to deep learning : from logical calculus to artificial intelligence / Sandro Skansi. - 1 online resource (XIII, 191 pages) : 38 illustrations. - - Undergraduate Topics in Computer Science, 1863-7310 . - Undergraduate topics in computer science, .
Academic Includes bibliographical references and index.
From Logic to Cognitive Science -- Mathematical and Computational Prerequisites -- Machine Learning Basics -- Feed-forward Neural Networks -- Modifications and Extensions to a Feed-forward Neural Network -- Convolutional Neural Networks -- Recurrent Neural Networks -- Autoencoders -- Neural Language Models -- An Overview of Different Neural Network Architectures -- Conclusion.
Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time;
Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
English
9783319730042 3319730045
10.1007/978-3-319-73004-2 doi
com.springer.onix.9783319730042 Springer Nature
GBB8K0004 bnb
Computer science., Machine learning., Neural networks (Computer science), Artificial intelligence, Mathematics.Data mining., Optical pattern recognition., Coding theory., Computer vision., Pattern perception., Neural networks (Computer science), Image processing., Data mining., Computer science., Coding theory., Computers, Computer Vision & Pattern Recognition.Mathematics, Applied.Computers, Information Theory.Computers, Computer Graphics.Pattern recognition., Mathematical modelling., Coding theory & cryptology., Image processing., Computers, Database ManagementData Mining.Data mining.,
Electronic books.
QA76.9.D343
Skansi, Sandro,
Introduction to deep learning : from logical calculus to artificial intelligence / Sandro Skansi. - 1 online resource (XIII, 191 pages) : 38 illustrations. - - Undergraduate Topics in Computer Science, 1863-7310 . - Undergraduate topics in computer science, .
Academic Includes bibliographical references and index.
From Logic to Cognitive Science -- Mathematical and Computational Prerequisites -- Machine Learning Basics -- Feed-forward Neural Networks -- Modifications and Extensions to a Feed-forward Neural Network -- Convolutional Neural Networks -- Recurrent Neural Networks -- Autoencoders -- Neural Language Models -- An Overview of Different Neural Network Architectures -- Conclusion.
Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time;
Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
English
9783319730042 3319730045
10.1007/978-3-319-73004-2 doi
com.springer.onix.9783319730042 Springer Nature
GBB8K0004 bnb
Computer science., Machine learning., Neural networks (Computer science), Artificial intelligence, Mathematics.Data mining., Optical pattern recognition., Coding theory., Computer vision., Pattern perception., Neural networks (Computer science), Image processing., Data mining., Computer science., Coding theory., Computers, Computer Vision & Pattern Recognition.Mathematics, Applied.Computers, Information Theory.Computers, Computer Graphics.Pattern recognition., Mathematical modelling., Coding theory & cryptology., Image processing., Computers, Database ManagementData Mining.Data mining.,
Electronic books.
QA76.9.D343