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Deep Learning
An engaging and accessible introduction to deep learning perfect for students and professionals In Deep Learning: A Practical Introduction, a team of distinguished researchers delivers a book complete with coverage of the theoretical and practical elements of deep learning. The book includes extensive examples, end-of-chapter exercises, homework, exam material, and a GitHub repository containing code and data for all provided examples. Combining contemporary deep learning theory with state-of-the-art tools, the chapters are structured to maximize accessibility for both beginning and intermediate students. The authors have included coverage of TensorFlow, Keras, and Pytorch. Readers will also...
Machine Learning and Data Mining in Pattern Recognition
This two-volume set LNAI 10934 and LNAI 10935 constitutes the refereed proceedings of the 14th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2018, held in New York, NY, USA in July 2018. The 92 regular papers presented in this two-volume set were carefully reviewed and selected from 298 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.
Machine Learning
Dig deep into the data with a hands-on guide to machine learning with updated examples and more! Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples for the most common machine learning techniques used by developers and technical professionals. The book contains a breakdown of each ML variant, explaining how it works and how it is used within certain industries, allowing readers to incorporate the presented techniques into their own work as they follow along. A core tenant of machine learning is a strong focus on data preparation, and a full exploration of the various types of learning algorithms illustrates how...
Practical Machine Learning in R
Guides professionals and students through the rapidly growing field of machine learning with hands-on examples in the popular R programming language Machine learning—a branch of Artificial Intelligence (AI) which enables computers to improve their results and learn new approaches without explicit instructions—allows organizations to reveal patterns in their data and incorporate predictive analytics into their decision-making process. Practical Machine Learning in R provides a hands-on approach to solving business problems with intelligent, self-learning computer algorithms. Bestselling author and data analytics experts Fred Nwanganga and Mike Chapple explain what machine learning is, dem...
2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe)
The general scope of the IEEE PES ISGT Europe Conference is to promote, share, and discuss innovations and developments in the field of smart grid technologies and applications Some of the relevant topics are Smart grid planning, design, and operation Demand response and real time pricing Electric vehicles and interactions with the grid Smart multi energy infrastructures and the environment Smart Grids and high voltage engineering Large scale integration of renewable energy and virtual power plants Information and communication technologies for smart grids, interoperability, and cyber security Wide area monitoring, protection, and control Institutional design for smart grids Market design and regulatory issues Smart grid maintenance and asset management Costs, risks, and benefits associated with smart grid technologies Big and open data, etc
Proceedings of International Conference on Intelligent Computing, Information and Control Systems
This book is a collection of papers presented at the International Conference on Intelligent Computing, Information and Control Systems (ICICCS 2020). It encompasses various research works that help to develop and advance the next-generation intelligent computing and control systems. The book integrates the computational intelligence and intelligent control systems to provide a powerful methodology for a wide range of data analytics issues in industries and societal applications. The book also presents the new algorithms and methodologies for promoting advances in common intelligent computing and control methodologies including evolutionary computation, artificial life, virtual infrastructures, fuzzy logic, artificial immune systems, neural networks and various neuro-hybrid methodologies. This book is pragmatic for researchers, academicians and students dealing with mathematically intransigent problems.
Terrains of Consciousness
TERRAINS OF CONSCIOUSNESS emerges from an Indian-German-Swiss research collaboration. The book makes a case for a phenomenology of globalization that pays attention to locally situated socioeconomic terrains, everyday practices, and cultures of knowledge. This is exemplified in relation to three topics: - the tension between 'terrain' and 'territory' in Defoe's 'Robinson Crusoe' as a pioneering work of the globalist mentality (chapter 1) - the relationship between established conceptions of feminism and the concrete struggles of women in India since the 19th century (chapter 2) - the exploration of urban space and urban life in writings on India's capital - from Ahmed Ali to Arundhati Roy (chapter 3).
Neural Networks
Renowned for its thoroughness and readability, this well-organized and completely up-to-date text remains the most comprehensive treatment of neural networks from an engineering perspective. Thoroughly revised. *NEW-New chapters now cover such areas as: - Support vector machines. - Reinforcement learning/neurodynamic programming. - Dynamically driven recurrent networks. *NEW-End-of-chapter problems revised, improved and expanded in number. Detailed solutions manual to accompany the text. *Extensive, state-of-the-art coverage exposes students to the many facets of neural networks and helps them appreciate the technologys capabilities and potential applications. *Detailed analysis of back-propagation learning and multi-layer perceptrons. *Explores the intricacies of the learning process-an essential component for understanding neural networks. *Considers recurrent networks, such as Hopfield networks, Boltzmann machines, and meanfield theory machines, as well as modular networks, temporal processing, and neurodynamics. *Integrates computer experiments throughout, giving students the opportunity to see how neural networks are designed and perform in practice. *Reinforces key concepts w
Robotics Simplified
A comprehensive outlook on all the concepts of Robotics for beginners KEY FEATURES ● Includes key concepts of robot modeling, control, and programming. ● Numerous examples and exercises on various aspects of robotics. ● Exposure to physical computing, robotic kinematics, trajectory planning, and motion control systems. DESCRIPTION ‘Robotics Simplified’ is a learner’s handbook that provides a thorough foundation around robotics, including all the basic concepts. The book takes you through a lot of essential topics about robotics, including robotic sensing, actuation, programming, motion control, and kinematic analysis of robotic manipulators. To begin with, the book prepares you w...
Advances and Priorities in Fisheries Technology
Proceedings of the Symposium on "Advances and Priorities in Fisheries Technology," held during 11-13 February, 1998, at Cochin, India.
