Deep Learning with Python

Quickly scale up to Quantum computing and Quantum machine learning foundations and related mathematics and expose them to different use cases that can be solved through Quantum based algorithms.This b

This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the w

This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models including deep neural networks and many of their

Although the ability to retain, process, and project prior experience onto future situations is indispensable, the human mind also possesses the ability to override experience and adapt to changing circumstances. Cognitive scientist Stellan Ohlsson analyzes three types of deep, non-monotonic cognitive change: creative insight, adaptation of cognitive skills by learning from errors, and conversion from one belief to another, incompatible belief. For each topic, Ohlsson summarizes past research, re-formulates the relevant research questions, and proposes information-processing mechanisms that answer those questions. The three theories are based on the principles of redistribution of activation, specialization of practical knowledge, and re-subsumption of declarative information. Ohlsson develops the implications of those mechanisms by scaling their effects with respect to time, complexity, and social interaction. The book ends with a unified theory of non-monotonic cognitive change that

Although the ability to retain, process, and project prior experience onto future situations is indispensable, the human mind also possesses the ability to override experience and adapt to changing circumstances. Cognitive scientist Stellan Ohlsson analyzes three types of deep, non-monotonic cognitive change: creative insight, adaptation of cognitive skills by learning from errors, and conversion from one belief to another, incompatible belief. For each topic, Ohlsson summarizes past research, re-formulates the relevant research questions, and proposes information-processing mechanisms that answer those questions. The three theories are based on the principles of redistribution of activation, specialization of practical knowledge, and re-subsumption of declarative information. Ohlsson develops the implications of those mechanisms by scaling their effects with respect to time, complexity, and social interaction. The book ends with a unified theory of non-monotonic cognitive change that

This easy-to-understand textbook presents a modern approach to learning numerical methods (or scientific computing), with a unique focus on the modeling and applications of the mathematical content. E

Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosyste