the Nest of Students

E. S. Gopi ... 256 pages - Publisher: Springer; (October, 2019) ... Language: English - ASIN: B07Z9MS1BZ by Amazon.

This book presents the complex topic of using computational intelligence for pattern recognition in a straightforward and applicable way, using Matlab to illustrate topics and concepts. The author covers computational intelligence tools like particle swarm optimization, bacterial foraging, simulated annealing, genetic algorithm, and artificial neural networks. The Matlab based illustrations along with the code are given for every topic. Readers get a quick basic understanding of various pattern recognition techniques using only the required depth in math. The Matlab program and algorithm are given along with the running text, providing clarity and usefulness of the various techniques.

Yen-Wei Chen, Lakhmi C. Jain ... 218 pages - Publisher: Springer; (November, 2019) ... Language: English - ASIN: B081R8DDN6 by Amazon.

This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems. Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data.

Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.

Yinyan Zhang, Shuai Li, Xuefeng Zhou ... 225 pages - Publisher: Springer; (November, 2019) ... Language: English - ISBN-10: 3030333833 - ISBN-13: 978-3030333836.

This book discusses methods and algorithms for the near-optimal adaptive control of nonlinear systems, including the corresponding theoretical analysis and simulative examples, and presents two innovative methods for the redundancy resolution of redundant manipulators with consideration of parameter uncertainty and periodic disturbances. It also reports on a series of systematic investigations on a near-optimal adaptive control method based on the Taylor expansion, neural networks, estimator design approaches, and the idea of sliding mode control, focusing on the tracking control problem of nonlinear systems under different scenarios. The book culminates with a presentation of two new redundancy resolution methods; one addresses adaptive kinematic control of redundant manipulators, and the other centers on the effect of periodic input disturbance on redundancy resolution. Each self-contained chapter is clearly written, making the book accessible to graduate students as well as academic and industrial researchers in the fields of adaptive and optimal control, robotics, and dynamic neural networks.

Gul Muhammad Khan ... 139 pages - Publisher: Springer; (October, 2017) - Language: English - ASIN: B076YWYQ38 by Amazon.

This book presents recent research on the evolution of artificial neural development, and searches for learning genes. It is fascinating to see how all biological cells share virtually the same traits, but humans have a decided edge over other species when it comes to intelligence. Although DNA decides the form each particular species takes, does it also account for intelligent behaviour in living beings.

The authors explore the factors that are perceived as intelligent behaviour in living beings and the incorporation of these factors in machines using genetic programming, which ultimately provides a platform for exploring the possibility of machines that can learn by themselves, i.e. that can “learn how to learn”. The book will be of interest not only to the specialized scientific community pursuing machine intelligence, but also general readers who would like to know more about the incorporation of intelligent behaviour in machines, inspired by the human brain.

Brian Larson ... 544 pages - Publisher: McGraw-Hill Education; (December, 2019) ... Language: English - ISBN-10: 126045861X - ISBN-13: 978-1260458619.

Explore, create, and manage highly interactive data visualizations using Microsoft Power BI: Extract meaningful business insights from your disparate enterprise data using the detailed information contained in this practical guide. Written by a recognized BI expert and bestselling author, Data Analysis with Microsoft Power BI teaches you the skills you need to interact with, author, and maintain robust visualizations and custom data models. Hands-on exercises based on real-life business scenarios clearly demonstrate each technique. Publishing your results to the Power BI Service (PowerBI.com) and Power BI Report Server are also fully covered.

Ian Pointer ... 220 pages - Publisher: O'Reilly Media; (October, 2019) ... Language: English - ISBN-10: 1492045357 - ISBN-13: 978-1492045359.

Delip Rao, Brian McMahan ... 256 pages - Publisher: O'Reilly Media; (February, 2019) ... Language: English - ISBN-10: 1491978236 - ISBN-13: 978-1491978238.

Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguita ... 403 pages - Publisher: Springer; (April, 2019) ... Language: English - ASIN: B07QD8SLQ4 by Amazon.

This book presents the original articles that have been accepted in the 2019 INNS Big Data and Deep Learning (INNS BDDL) international conference, a major event for researchers in the field of artificial neural networks, big data and related topics, organized by the International Neural Network Society and hosted by the University of Genoa. In 2019 INNS BDDL has been held in Sestri Levante (Italy) from April 16 to April 18. More than 80 researchers from 20 countries participated in the INNS BDDL in April 2019. In addition to regular sessions, INNS BDDL welcomed around 40 oral communications, 6 tutorials have been presented together with 4 invited plenary speakers. This book covers a broad range of topics in big data and deep learning, from theoretical aspects to state-of-the-art applications. This book is directed to both Ph.D. students and Researchers in the field in order to provide a general picture of the state-of-the-art on the topics addressed by the conference.

Witold Pedrycz, Shyi-Ming Chen ... 342 pages - Publisher: Springer; (October, 2019) ... Language: English - ISBN-10: 3030317552 - ISBN-13: 978-3030317553.

This book introduces readers to the fundamental concepts of deep learning and offers practical insights into how this learning paradigm supports automatic mechanisms of structural knowledge representation. It discusses a number of multilayer architectures giving rise to tangible and functionally meaningful pieces of knowledge, and shows how the structural developments have become essential to the successful delivery of competitive practical solutions to real-world problems. The book also demonstrates how the architectural developments, which arise in the setting of deep learning, support detailed learning and refinements to the system design. Featuring detailed descriptions of the current trends in the design and analysis of deep learning topologies, the book offers practical guidelines and presents competitive solutions to various areas of language modeling, graph representation, and forecasting.

Richard Jiang, Chang-Tsun Li, Danny Crookes, Weizhi Meng, Christophe Rosenberger ... 320 pages - Publisher: Springer; January, 2020) ... Language: English - ASIN: B084D81NNG by Amazon.

This book highlights new advances in biometrics using deep learning toward deeper and wider background, deeming it “Deep Biometrics”. The book aims to highlight recent developments in biometrics using semi-supervised and unsupervised methods such as Deep Neural Networks, Deep Stacked Autoencoder, Convolutional Neural Networks, Generative Adversary Networks, and so on. The contributors demonstrate the power of deep learning techniques in the emerging new areas such as privacy and security issues, cancellable biometrics, soft biometrics, smart cities, big biometric data, biometric banking, medical biometrics, healthcare biometrics, and biometric genetics, etc. The goal of this volume is to summarize the recent advances in using Deep Learning in the area of biometric security and privacy toward deeper and wider applications.

Witold Pedrycz, Shyi-Ming Chen ... 292 pages - Publisher: Springer; (November, 2019) ... Language: English - ASIN: B07ZX66TYJ by Amazon.

This book offers a timely reflection on the remarkable range of algorithms and applications that have made the area of deep learning so attractive and heavily researched today. Introducing the diversity of learning mechanisms in the environment of big data, and presenting authoritative studies in fields such as sensor design, health care, autonomous driving, industrial control and wireless communication, it enables readers to gain a practical understanding of design. The book also discusses systematic design procedures, optimization techniques, and validation processes.

Witold Pedrycz, Shyi-Ming Chen ... 360 pages - Publisher: Springer; (October, 2019) ... Language: English - ASIN: B07ZMY46RV by Amazon.

This book presents a wealth of deep-learning algorithms and demonstrates their design process. It also highlights the need for a prudent alignment with the essential characteristics of the nature of learning encountered in the practical problems being tackled. Intended for readers interested in acquiring practical knowledge of analysis, design, and deployment of deep learning solutions to real-world problems, it covers a wide range of the paradigm’s algorithms and their applications in diverse areas including imaging, seismic tomography, smart grids, surveillance and security, and health care, among others. Featuring systematic and comprehensive discussions on the development processes, their evaluation, and relevance, the book offers insights into fundamental design strategies for algorithms of deep learning.

Radek Silhavy ... 501 pages - Publisher: Springer; (May, 2018) ... Language: English - ASIN: B07DBK5RFZ by Amazon.

This book presents the latest trends and approaches in artificial intelligence research and its application to intelligent systems. It discusses hybridization of algorithms, new trends in neural networks, optimisation algorithms and real-life issues related to the application of artificial methods. The book constitutes the second volume of the refereed proceedings of the Artificial Intelligence and Algorithms in Intelligent Systems of the 7th Computer Science On-line Conference 2018 (CSOC 2018), held online in April 2018.

Thomas Mailund ... 386 pages - Publisher: Apress; (March, 2017) ... Language: English - AmazonSIN: B06XHZVBF1.

Pramod Singh, Avinash Manure ... 164 pages - Publisher: Apress; (December, 2019) ... Language: English - ASIN: B082X9CM42 by Amazon.

Sandro Skansi ... 140 pages - Publisher: Springer; (January, 2020) ... Language: English - ASIN: B0846GYCDD by Amazon.

This stimulating text/reference presents a philosophical exploration of the conceptual foundations of deep learning, presenting enlightening perspectives that encompass such diverse disciplines as computer science, mathematics, logic, psychology, and cognitive science. The text also highlights select topics from the fascinating history of this exciting field, including the pioneering work of Rudolf Carnap, Warren McCulloch, Walter Pitts, Bulcsú László, and Geoffrey Hinton.

Topics and features: Provides a brief history of mathematical logic, and discusses the critical role of philosophy, psychology, and neuroscience in the history of AI + Presents a philosophical case for the use of fuzzy logic approaches in AI + Investigates the similarities and differences between the Word2vec word embedding algorithm, and the ideas of Wittgenstein and Firth on linguistics + Examines how developments in machine learning provide insights into the philosophical challenge of justifying inductive inferences + Debates, with reference to philosophical anthropology, whether an advanced general artificial intelligence might be considered as a living being + Investigates the issue of computational complexity through deep-learning strategies for understanding AI-complete problems and developing strong AI + Explores philosophical questions at the intersection of AI and transhumanism. This inspirational volume will rekindle a passion for deep learning in those already experienced in coding and studying this discipline, and provide a philosophical big-picture perspective for those new to the field.

M. Arif Wani, Farooq Ahmad Bhat, Saduf Afzal, Asif Iqbal Khan ... 149 pages - Publisher: Springer; (March, 2019) ... Language: English - ASIN: B07PN2QZKM by Amazon.

This book introduces readers to both basic and advanced concepts in deep network models. It covers state-of-the-art deep architectures that many researchers are currently using to overcome the limitations of the traditional artificial neural networks. Various deep architecture models and their components are discussed in detail, and subsequently illustrated by algorithms and selected applications. In addition, the book explains in detail the transfer learning approach for faster training of deep models; the approach is also demonstrated on large volumes of fingerprint and face image datasets. In closing, it discusses the unique set of problems and challenges associated with these models.

Sebastian Raschka, Vahid Mirjalili ... 770 pages - Publisher: Packt Publishing; (December, 2019) ... Language: English - ISBN-10: 1789955750 - ISBN-13: 978-1789955750.

Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself. Updated for TensorFlow 2.0, this new third edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs. Finally, this book also explores a subfield of natural language processing (NLP) called sentiment analysis, helping you learn how to use machine learning algorithms to classify documents.This book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.

Tom Taulli ... 200 pages - Publisher: Apress; (August, 2019) ... Language: English - ISBN-10: 1484250273 - ISBN-13: 978-1484250273.

Artificial intelligence touches nearly every part of your day. While you may initially assume that technology such as smart speakers and digital assistants are the extent of it, AI has in fact rapidly become a general-purpose technology, reverberating across industries including transportation, healthcare, financial services, and many more. In our modern era, an understanding of AI and its possibilities for your organization is essential for growth and success. Artificial Intelligence Basics has arrived to equip you with a fundamental, timely grasp of AI and its impact. Author Tom Taulli provides an engaging, non-technical introduction to important concepts such as machine learning, deep learning, natural language processing (NLP), robotics, and more. In addition to guiding you through real-world case studies and practical implementation steps, Taulli uses his expertise to expand on the bigger questions that surround AI. These include societal trends, ethics, and future impact AI will have on world governments, company structures, and daily life. Google, Amazon, Facebook, and similar tech giants are far from the only organizations on which artificial intelligence has had―and will continue to have―an incredibly significant result. AI is the present and the future of your business as well as your home life. Strengthening your prowess on the subject will prove invaluable to your preparation for the future of tech, and Artificial Intelligence Basics is the indispensable guide that you’ve been seeking.

Abdulhamit Subasi ... 456 pages - Publisher: Academic Press; (March, 2019) ... Language: English - ISBN-10: 0128174447 - ISBN-13: 978-0128174449.

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine learning and biomedical signal processing methods can be used in biomedical signal analysis. Different machine learning applications in biomedical signal analysis, including those for electrocardiogram, electroencephalogram and electromyogram are described in a practical and comprehensive way, helping readers with limited knowledge. Sections cover biomedical signals and machine learning techniques, biomedical signals, such as electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG), different signal-processing techniques, signal de-noising, feature extraction and dimension reduction techniques, such as PCA, ICA, KPCA, MSPCA, entropy measures, and other statistical measures, and more. This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need a cogent resource on the most recent and promising machine learning techniques for biomedical signals analysis.