Machine learning Books
£40.49
De Gruyter Machine Learning and Visual Perception
Book Synopsis
£37.88
De Gruyter Quantum Machine Learning
Quantum-enhanced machine learning refers to quantum algorithms that solve tasks in machine learning, thereby improving a classical machine learning method. Such algorithms typically require one to encode the given classical dataset into a quantum computer, so as to make it accessible for quantum information processing. After this, quantum information processing routines can be applied and the result of the quantum computation is read out by measuring the quantum system. While many proposals of quantum machine learning algorithms are still purely theoretical and require a full-scale universal quantum computer to be tested, others have been implemented on small-scale or special purpose quantum devices.
£110.20
De Gruyter Internet of Things and Machine Learning in
Book SynopsisAgriculture is one of the most fundamental human activities. As the farming capacity has expanded, the usage of resources such as land, fertilizer, and water has grown exponentially, and environmental pressures from modern farming techniques have stressed natural landscapes. Still, by some estimates, worldwide food production needs to increase to keep up with global food demand. Machine Learning and the Internet of Things can play a promising role in the Agricultural industry, and help to increase food production while respecting the environment. This book explains how these technologies can be applied, offering many case studies developed in the research world.
£136.09
De Gruyter Machine Learning for Sustainable Development
Book SynopsisThe book will focus on the applications of machine learning for sustainable development. Machine learning (ML) is an emerging technique whose diffusion and adoption in various sectors (such as energy, agriculture, internet of things, infrastructure) will be of enormous benefit. The state of the art of machine learning models is most useful for forecasting and prediction of various sectors for sustainable development.
£85.12
De Gruyter Bitcoin: A Game-Theoretic Analysis
Book SynopsisThe definitive guide to the game-theoretic and probabilistic underpinning for Bitcoin’s security model. The book begins with an overview of probability and game theory. Nakamoto Consensus is discussed in both practical and theoretical terms. This volume: Describes attacks and exploits with mathematical justifications, including selfish mining. Identifies common assumptions such as the Market Fragility Hypothesis, establishing a framework for analyzing incentives to attack. Outlines the block reward schedule and economics of ASIC mining. Discusses how adoption by institutions would fundamentally change the security model. Analyzes incentives for double-spend and sabotage attacks via stock-flow models. Overviews coalitional game theory with applications to majority takeover attacks Presents Nash bargaining with application to unregulated environments This book is intended for students or researchers wanting to engage in a serious conversation about the future viability of Bitcoin as a decentralized, censorship-resistant, peer-to-peer electronic cash system.
£53.55
De Gruyter Digital Twins: Internet of Things, Machine
Book SynopsisThis book explores the significance, challenges and benefits of digital twin technologies; it focuses in particular on various architectures, applications and challenges in the implementation of digital twins to Machine Learning and Internet of Things capabilities. Through the analysis of smart city and smart manufacturing case studies, the book explores the benefits of digital technologies in the Industry 4.0 Era.
£116.62
De Gruyter Quantum Computing and Artificial Intelligence:
Book SynopsisThis book is to explore and explain the strategically sound capabilities at the synchronization between quantum computing and artificial intelligence (AI). The reader will be presented with an introduction and a deeper review of the technological trends and transitions being unearthed in the quantum computing and AI domains.
£123.50
De Gruyter Quantum-Safe Cryptography Algorithms and
Book SynopsisQuantum computers have demonstrated that they have the inherent potential to outperform classical computers in many areas. One of the major impacts is that the currently available cryptography algorithms are bound to no longer hold once quantum computers are able to compute at full speed. This book presents an overview of all the cross-disciplinary developments in cybersecurity that are being generated by the advancements in quantum computing.
£123.50
de Gruyter Green Composites Manufacturing
Book Synopsis
£134.42
De Gruyter Toward Artificial General Intelligence: Deep
Book SynopsisArtifi cial Intelligence (AI) has been an exciting fi eld of study and research in educational institutions and research labs across the globe. Technology giants and IT organizations invest heavily on AI technologies and tools with the aim of preciselyautomating a variety of simple as well as complicated business operations acrossindustry verticals. This book covers the latest trends and transitions happening in thefuturistic AI domain. The book also focuses on machine and deep learning (ML/DL)algorithms, which are, undoubtedly, the mainstream implementation technologies ofstate-of-the-art AI systems and services. Also, there are chapters on computer vision(CV) and natural language processing (NLP), the primary use cases and applicationsof AI. The book has well-written chapters for demystifying AI model engineeringmethods. Further on, our esteemed readers can fi nd details on AI model evaluation,optimization, deployment and observability. Finally, the book deals and describesgenerative AI, the latest buzzword in the IT industry. The book presents the recent ground-breaking changes taking place in the aspects of AI model building, hosting, running and maintaining in cloud environments, articulates and accentuates the most recent developments taking place in the domain of Artifi cial Intelligence, covers the noteworthy innovations and disruptions towards Generative Artifi cial Intelligence (Generative AI), explains the breakthrough innovations and disruptions towards Artifi cial General Intelligence (AGI) and delineates an engaging discussion of Natural Language Processing, Neuromorphic Systems and Biometrics.
£88.88
De Gruyter Industrial Quantum Computing
Book Synopsis
£106.12
De Gruyter Mathematical Optimization for Machine Learning
Book Synopsis
£138.22
De Gruyter Zum Automatischen Erlernen Von Beschreibungen Für
Book Synopsis
£121.84
Springer International Publishing AG Machine Learning for the Quantified Self: On the
Book SynopsisThis book explains the complete loop to effectively use self-tracking data for machine learning. While it focuses on self-tracking data, the techniques explained are also applicable to sensory data in general, making it useful for a wider audience. Discussing concepts drawn from from state-of-the-art scientific literature, it illustrates the approaches using a case study of a rich self-tracking data set. Self-tracking has become part of the modern lifestyle, and the amount of data generated by these devices is so overwhelming that it is difficult to obtain useful insights from it. Luckily, in the domain of artificial intelligence there are techniques that can help out: machine-learning approaches allow this type of data to be analyzed. While there are ample books that explain machine-learning techniques, self-tracking data comes with its own difficulties that require dedicated techniques such as learning over time and across users.Table of ContentsIntroduction.- Basics of Sensory Data.- Feature Engineering based on Sensory Data.- Predictive Modeling without Notion of Time.- Predictive Modeling with Notion of Time.- Reinforcement Learning to Provide Feedback and Support.- Discussion.
£132.99
Springer International Publishing AG Machine Learning for Text
Book SynopsisText analytics is a field that lies on the interface of information retrieval,machine learning, and natural language processing, and this textbook carefully covers a coherently organized framework drawn from these intersecting topics. The chapters of this textbook is organized into three categories:- Basic algorithms: Chapters 1 through 7 discuss the classical algorithms for machine learning from text such as preprocessing, similarity computation, topic modeling, matrix factorization, clustering, classification, regression, and ensemble analysis.- Domain-sensitive mining: Chapters 8 and 9 discuss the learning methods from text when combined with different domains such as multimedia and the Web. The problem of information retrieval and Web search is also discussed in the context of its relationship with ranking and machine learning methods. - Sequence-centric mining: Chapters 10 through 14 discuss various sequence-centric and natural language applications, such as feature engineering, neural language models, deep learning, text summarization, information extraction, opinion mining, text segmentation, and event detection. This textbook covers machine learning topics for text in detail. Since the coverage is extensive,multiple courses can be offered from the same book, depending on course level. Even though the presentation is text-centric, Chapters 3 to 7 cover machine learning algorithms that are often used indomains beyond text data. Therefore, the book can be used to offer courses not just in text analytics but also from the broader perspective of machine learning (with text as a backdrop). This textbook targets graduate students in computer science, as well as researchers, professors, and industrial practitioners working in these related fields. This textbook is accompanied with a solution manual for classroom teaching.Trade Review“The book discusses many key technologies used today in social media, such as opinion mining or event detection. One of the most promising new technologies, deep learning, is discussed as well. This book is an excellent resource for programmers and graduate students interested in becoming experts in the text mining field. … Summing Up: Recommended. Graduate students, researchers, and professionals.” (J. Brzezinski, Choice, Vol. 56 (04), December, 2018)Table of Contents1 An Introduction to Text Analytics.- 2 Text Preparation and Similarity Computation.- 3 Matrix Factorization and Topic Modeling.- 4 Text Clustering.- 5 Text Classification: Basic Models.- 6 Linear Models for Classification and Regression.- 7 Classifier Performance and Evaluation.- 8 Joint Text Mining with Heterogeneous Data.- 9 Information Retrieval and Search Engines.- 10 Text Sequence Modeling and Deep Learning.- 11 Text Summarization.- 12 Information Extraction.- 13 Opinion Mining and Sentiment Analysis.- 14 Text Segmentation and Event Detection.
£58.49
Springer International Publishing AG Human and Machine Learning: Visible, Explainable, Trustworthy and Transparent
With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different applications. However, because of the nature of “black-box” in ML methods, ML still needs to be interpreted to link human and machine learning for transparency and user acceptance of delivered solutions. This edited book addresses such links from the perspectives of visualisation, explanation, trustworthiness and transparency. The book establishes the link between human and machine learning by exploring transparency in machine learning, visual explanation of ML processes, algorithmic explanation of ML models, human cognitive responses in ML-based decision making, human evaluation of machine learning and domain knowledge in transparent ML applications. This is the first book of its kind to systematically understand the current active research activities and outcomes related to human and machine learning. The book will not only inspire researchers to passionately develop new algorithms incorporating human for human-centred ML algorithms, resulting in the overall advancement of ML, but also help ML practitioners proactively use ML outputs for informative and trustworthy decision making. This book is intended for researchers and practitioners involved with machine learning and its applications. The book will especially benefit researchers in areas like artificial intelligence, decision support systems and human-computer interaction.
£80.99
Wiley-VCH Verlag GmbH Maschinelles Lernen fur Dummies
Book SynopsisAlgorithmen für künstliches Lernen verstehen Maschinelles Lernen ist eines der wichtigsten Teilgebiete der künstlichen Intelligenz und das Verstehen und Entwickeln von passenden Algorithmen bleibt die große Herausforderung. Dieses Buch bietet einen außergewöhnlich umfassenden Überblick über die neuesten Algorithmen und die bereits bewährten Verfahren. Jörn Fischer beschreibt nicht nur deren Funktionsweise, sondern gibt für alle Bereiche verständliche Beispiele, die detailliert beschrieben und leicht nachvollziehbar sind. Außerdem werden hilfreiche Methoden zur Fehlersuche und -beseitigung an die Hand gegeben. Sie erfahren Wie Sie mit Python und Frameworks startenWie Sie Optimierung, Clustering und Klassifizierung umsetzen Wie generative Methoden und Reinforcement Learning funktionieren Wie neuronale Netze arbeiten und erklärbar werden
£22.46
Springer Fachmedien Wiesbaden Theoretische Informatik: Formale Sprachen,
Book SynopsisDas Ziel dieses Buches ist es, den Leser an den Grundlagen der Informatik zu begeistern. Um dies zu erreichen, bieten wir außer der üblichen rigorosen und detaillierten Präsentation eine leicht verständliche und anschauliche Darstellung der Grundkonzepte und Ideen und erweitern die klassischen Themen wie Berechenbarkeit und Komplexität um die faszinierenden Errungenschaften neuer Gebiete wie Randomisierung, Kryptographie und Kommunikation in Netzen.Table of ContentsAlphabete, Wörter, Sprachen und Aufgaben - Endliche Automaten - Turingmaschinen - Berechenbarkeit - Komplexitätstheorie - Algorithmik für schwere Probleme - Randomisierung - Kommunikation und Kryptographie - Grammatik und Chomsky-Hierarchie
£42.74
Springer Fachmedien Wiesbaden Machine Learning Systems for Multimodal Affect Recognition
Book SynopsisMarkus Kächele offers a detailed view on the different steps in the affective computing pipeline, ranging from corpus design and recording over annotation and feature extraction to post-processing, classification of individual modalities and fusion in the context of ensemble classifiers. He focuses on multimodal recognition of discrete and continuous emotional and medical states. As such, specifically the peculiarities that arise during annotation and processing of continuous signals are highlighted. Furthermore, methods are presented that allow personalization of datasets and adaptation of classifiers to new situations and persons. Table of ContentsClassification and Regression Approaches.- Applications and Affective Corpora.- Modalities and Feature Extraction.- Machine Learning for the Estimation of Affective Dimensions.- Adaptation and Personalization of Classifiers.- Experimental Validation.
£49.49
Springer Fachmedien Wiesbaden Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces
Book SynopsisPascal Laube presents machine learning approaches for three key problems of reverse engineering of defective structured surfaces: parametrization of curves and surfaces, geometric primitive classification and inpainting of high-resolution textures. The proposed methods aim to improve the reconstruction quality while further automating the process. The contributions demonstrate that machine learning can be a viable part of the CAD reverse engineering pipeline.Table of ContentsMachine Learning Methods for Parametrization in Curve and Surface Approximation.- Classification of Geometric Primitives in Point Clouds.- Image Inpainting for High-resolution Textures Using CNN Texture Synthesis.
£49.49
Springer Fachmedien Wiesbaden Reinforcement Learning with Hybrid Quantum
Book SynopsisThis book explores the combination of Reinforcement Learning and Quantum Computing in the light of complex attacker-defender scenarios. Reinforcement Learning has proven its capabilities in different challenging optimization problems and is now an established method in Operations Research. However, complex attacker-defender scenarios have several characteristics that challenge Reinforcement Learning algorithms, requiring enormous computational power to obtain the optimal solution. The upcoming field of Quantum Computing is a promising path for solving computationally complex problems. Therefore, this work explores a hybrid quantum approach to policy gradient methods in Reinforcement Learning. It proposes a novel quantum REINFORCE algorithm that enhances its classical counterpart by Quantum Variational Circuits. The new algorithm is compared to classical algorithms regarding the convergence speed and memory usage on several attacker-defender scenarios with increasing complexity. In addition, to study its applicability on today's NISQ hardware, the algorithm is evaluated on IBM's quantum computers, which is accompanied by an in-depth analysis of the advantages of Quantum Reinforcement Learning.Table of ContentsMotivation: Complex Attacker-Defender Scenarios - The eternal conflict., The Information Game - A special Attacker-Defender Scenario., Reinforcement Learning and Bellman’s Principle of Optimality., Quantum Reinforcement Learning - Connecting Reinforcement Learning and Quantum Computing.- Approximation in Quantum Computing.- Advanced Quantum Policy Approximation in Policy Gradient Rein-forcement Learning.- Applying Quantum REINFORCE to the Information Game.- Evaluating quantum REINFORCE on IBM’s Quantum Hardware.- Future Steps in Quantum Reinforcement Learning for Complex Scenarios.- Conclusion.
£66.49
Springer Fachmedien Wiesbaden Machine Learning Algorithm for Fatigue Fields in
Book SynopsisFatigue failure of structures used in transportation, industry, medical equipment, and electronic components needs to build a link between cutting-edge experimental characterization and probabilistically grounded numerical and artificially intelligent tools. The physics involved in this process chain is computationally prohibitive to comprehend using traditional computation methods. Using machine learning and Bayesian statistics, a defect-correlated estimate of fatigue strength was developed. Fatigue, which is a random variable, is studied in a Bayesian-based machine learning algorithm. The stress-life model was used based on the compatibility condition of life and load distributions. The defect-correlated assessment of fatigue strength was established using the proposed machine learning and Bayesian statistics algorithms. It enabled the mapping of structural and process-induced fatigue characteristics into a geometry-independent load density chart across a wide range of fatigue regimes.Table of ContentsIntroduction and objectives.- Background on process-property relationship.- Training and testing data.- Estimation of lifetime trends based on FEM.- Bayesian inferences of fatigue-related influences.- Summary and outlook.- References.
£71.24
Springer Fachmedien Wiesbaden Machine Learning under Malware Attack
Book SynopsisMachine learning has become key in supporting decision-making processes across a wide array of applications, ranging from autonomous vehicles to malware detection. However, while highly accurate, these algorithms have been shown to exhibit vulnerabilities, in which they could be deceived to return preferred predictions. Therefore, carefully crafted adversarial objects may impact the trust of machine learning systems compromising the reliability of their predictions, irrespective of the field in which they are deployed. The goal of this book is to improve the understanding of adversarial attacks, particularly in the malware context, and leverage the knowledge to explore defenses against adaptive adversaries. Furthermore, to study systemic weaknesses that can improve the resilience of machine learning models. Table of ContentsThe Beginnings of Adversarial ML.- Framework for Adversarial Malware Evaluation.- Problem-Space Attacks.- Feature-Space Attacks.- Closing Remarks.
£61.74
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Transactions on Large-Scale Data- and Knowledge-Centered Systems XLV: Special Issue on Data Management and Knowledge Extraction in Digital Ecosystems
Book SynopsisThe LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing (e.g., computing resources, services, metadata, data sources) across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. This, the 45th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains eight revised selected regular papers. Topics covered include data analysis, information extraction, blockchains, and big data.Table of ContentsInteroperable Data Extraction and Analytics Queries over Blockchains.- Exploiting Twitter for Informativeness Classification in Disaster Situations.- COTILES: Leveraging Content and Structure for Evolutionary Community Detection.- A Weighted Feature-Based Image Quality Assessment Framework in Real-Time.- Sharing Knowledge in Digital Ecosystems Using Semantic Multimedia Big Data.- Facilitating and Managing Machine Learning and Data Analysis Tasks in Big Data Environments Using Web and Microservice Technologies.- Stable Marriage Matching for Homogenizing Load Distribution in a Cloud Data Center.- A Sentiment Analysis Software Framework for the Support of Business Information Architecture in the Tourist Sector
£71.24
Springer Fachmedien Wiesbaden Microsoft Conversational AI-Platform für
Book SynopsisErstellen Sie einen Chatbot mit der Microsoft Conversational AI-Plattform. In diesem Buch lernen Sie Schritt für Schritt, wie Sie Zeit und Geld sparen können, indem Sie Chatbots in die Strategie Ihres Unternehmens integrieren. Sie werden lernen, wie Sie jede Phase der Entwicklung beherrschen, von der Zusammenarbeit an einem Chatbot in einem End-to-End-Szenario über die erste Mock-up-Phase bis hin zur Einsatz- und Bewertungsphase. Microsoft hat ein Cloud-Service-Ökosystem für die Ausführung von künstlichen Intelligenz-Workloads in öffentlichen Cloud-Szenarien und eine robuste KI-Plattform aufgebaut, die eine breite Palette von Diensten für konversationelle künstliche Intelligenz-Lösungen wie Chatbots bietet. Die Entwicklung eines Chatbots erfordert nicht nur Programmierkenntnisse von Entwicklern, sondern auch besondere Überlegungen, einschließlich des Inputs von Geschäftsinteressenten wie Fachexperten und Power-Usern. Sie werden anhand von Beispielen lernen, wie Sie eine Reihe von Tools und Diensten nutzen können, um die Kluft zwischen Unternehmen und Technik zu überbrücken. Sie werden lernen, wie Sie Geschäftsanforderungen erfolgreich in umsetzbare IT- und technische Anforderungen umwandeln können. Sie lernen den Bot Framework Composer kennen, der es Power-Usern ermöglicht, die Erstellung eines Chatbots zu initiieren, der dann an das Entwicklungsteam weitergegeben werden kann, um durch Code weitere Funktionen hinzuzufügen. Der Prozess der Aufteilung der Implementierungsaufgaben und des Arbeitsaufwands zwischen Power-Usern, die einen Low-Code- oder No-Code-Ansatz verwenden, und Entwicklern, die die erweiterten Funktionen für den Chatbot entwickeln, wird ebenfalls behandelt.Was Sie lernen werden: Verstehen Sie Microsofts umfassendes KI-Ökosystem und seine Dienste und Lösungen Erkennen Sie, welche Lösungen und Dienste in jedem Geschäftsszenario angewendet werden sollten Entdecken Sie No-Code-/Low-Code-Ansätze für die Erstellung von Chatbots Entwickeln Sie Chatbots unter Verwendung des Conversational AI Stacks Richten Sie Geschäft und Entwicklung für verbesserte Chatbot-Ergebnisse und kürzere Markteinführungszeiten aus Dieses Buch richtet sich an Entwickler und Power-User, die Chatbots erstellen möchten. Ein Verständnis für die Grundprinzipien des Programmierens moderner Webanwendungen (.NET oder JavaScript) wird vorausgesetzt.Table of ContentsKapitel 1: Einführung in die Microsoft Conversational AI Platform Kapitel 2: Einführung in das Microsoft Bot Framework Kapitel 3: Einführung in Azure Cognitive Services Kapitel 4: Gestaltungsprinzipien eines Chatbots Kapitel 5: Aufbau eines Chatbots Kapitel 6: Testen eines Chatbots Kapitel 7: Veröffentlichung eines Chatbots Kapitel 8: Verbinden eines Chatbots mit Kanälen
£34.19
£17.99
Springer Transactions on LargeScale Data and
Book Synopsis
£49.49
Springer Fachmedien Wiesbaden Grundkurs Theoretische Informatik: Eine
Book SynopsisDiese Theorie-Einführung hat konsequent aktuelle Anwendungen im Blick. Seien es Suchmaschinen, Workflow-Managementsysteme, Web Services, Verschlüsselung von Informationen, Authentifizierungsprotokolle – all diese Technologien beruhen auf theoretischen Grundlagen der Informatik. So trägt das Buch dazu bei, dass Studierende die Grundlagen der Theoretischen Informatik nicht nur kennen lernen, sondern auch anwenden können, um effektiv und produktiv an informationstechnischen Problemlösungen mitwirken zu können. Wegen seiner speziellen inhaltlichen und didaktischen Qualität ist das Buch neben dem Einsatz in der Lehre auch für das Selbststudium geeignet.Table of ContentsEndliche Automaten und reguläre Sprachen - Kontextfreie Sprachen und Kellerautomaten - Turingmaschinen und Berechenbarkeit - Grenzen von Algorithmen - Komplexität, Effizienz und Effektivität - Vielfältige Anwendungen theoretischer Konzepte in der Praxis
£42.74
JOVIS Verlag Hey Computer!: Icons of Architecture, Rebuilt by
Book SynopsisArtificial neuronal networks open up radical new pathways for image creation. On the basis of textual prompts, machine-learning algorithms like Midjourney and Stable Diffusion generate imagery that is simultaneously familiar and alien. Graphic designer Floyd Schulze uses this rapidly developing technology to recreate architectural icons. In an accompanying essay, Georg Vrachliotis takes up the topic on the theoretical level. Hey Computer! is the first book to deal with AI-generated architectural imagery from an artistic perspective.
£20.70
BPB Publications Machine Learning for Beginners - 2nd Edition:
Book Synopsis
£26.59
BPB Publications Building Transformer Models with PyTorch 2.0
Book SynopsisThis book covers transformer architecture for various applications including NLP, computer vision, speech processing, and predictive modeling with tabular data. It is a valuable resource for anyone looking to harness the power of transformer architecture in their machine learning projects. The book provides a step-by-step guide to building transformer models from scratch and fine-tuning pre-trained open-source models. It explores foundational model architecture, including GPT, VIT, Whisper, TabTransformer, Stable Diffusion, and the core principles for solving various problems with transformers. The book also covers transfer learning, model training, and fine-tuning, and discusses how to utilize recent models from Hugging Face.
£26.59
BPB Publications Mastering MLOps Architecture: From Code to
Book Synopsis
£29.92
BPB Publications Optimizing AI and Machine Learning Solutions
Book SynopsisThis book approaches data science solution building using a principled framework and case studies with extensive hands-on guidance. It will teach the readers optimization at each step, whether it is problem formulation or hyperparameter tuning for deep learning models. This book keeps the reader pragmatic and guides them toward practical solutions by discussing the essential ML concepts, including problem formulation, data preparation, and evaluation techniques. Further, the reader will be able to learn how to apply model optimization with advanced algorithms, hyperparameter tuning, and strategies against overfitting. They will also benefit from deep learning by optimizing models for image processing, natural language processing, and specialized applications. The reader can put theory into practice with hands-on case studies and code examples, reinforcing their understanding.
£29.92
BPB Publications Generative AI for Everyone
Book SynopsisExplore the entire spectrum of generative AI, from fundamental AI concepts to advanced LLM applications. Includes practical examples, code snippets, and real-world case studies to enhance learning and understanding.
£33.24
New India Publishing Agency Digital Technologies for Agriculture
Book Synopsis
£186.16
World Scientific Publishing Co Pte Ltd Introduction To Genetic Algorithms For Scientists
Book SynopsisThis invaluable book has been designed to be useful to most practising scientists and engineers, whatever their field and however rusty their mathematics and programming might be. The approach taken is largely practical, with algorithms being presented in full and working code (in BASIC, FORTRAN, PASCAL AND C) included on a floppy disk to help the reader get up and running as quickly as possible. The text could also be used as part of an undergraduate course on search and optimisation. Student exercises are included at the end of several of the chapters, many of which are computer-based and designed to encourage exploration of the method.Table of ContentsImproving the algorithm; foundations; advanced operators; writing a genetic algorithm; applications of genetic algorithms.
£38.95
World Scientific Publishing Co Pte Ltd Linear Algebra And Optimization With Applications
Book SynopsisThis book provides the mathematical fundamentals of linear algebra to practicers in computer vision, machine learning, robotics, applied mathematics, and electrical engineering. By only assuming a knowledge of calculus, the authors develop, in a rigorous yet down to earth manner, the mathematical theory behind concepts such as: vectors spaces, bases, linear maps, duality, Hermitian spaces, the spectral theorems, SVD, and the primary decomposition theorem. At all times, pertinent real-world applications are provided. This book includes the mathematical explanations for the tools used which we believe that is adequate for computer scientists, engineers and mathematicians who really want to do serious research and make significant contributions in their respective fields.
£162.00
World Scientific Publishing Co Pte Ltd Linear Algebra And Optimization With Applications
Book SynopsisThis book provides the mathematical fundamentals of linear algebra to practicers in computer vision, machine learning, robotics, applied mathematics, and electrical engineering. By only assuming a knowledge of calculus, the authors develop, in a rigorous yet down to earth manner, the mathematical theory behind concepts such as: vectors spaces, bases, linear maps, duality, Hermitian spaces, the spectral theorems, SVD, and the primary decomposition theorem. At all times, pertinent real-world applications are provided. This book includes the mathematical explanations for the tools used which we believe that is adequate for computer scientists, engineers and mathematicians who really want to do serious research and make significant contributions in their respective fields.
£81.00
World Scientific Publishing Co Pte Ltd Linear Algebra And Optimization With Applications
Book SynopsisVolume 2 applies the linear algebra concepts presented in Volume 1 to optimization problems which frequently occur throughout machine learning. This book blends theory with practice by not only carefully discussing the mathematical under pinnings of each optimization technique but by applying these techniques to linear programming, support vector machines (SVM), principal component analysis (PCA), and ridge regression. Volume 2 begins by discussing preliminary concepts of optimization theory such as metric spaces, derivatives, and the Lagrange multiplier technique for finding extrema of real valued functions. The focus then shifts to the special case of optimizing a linear function over a region determined by affine constraints, namely linear programming. Highlights include careful derivations and applications of the simplex algorithm, the dual-simplex algorithm, and the primal-dual algorithm. The theoretical heart of this book is the mathematically rigorous presentation of various nonlinear optimization methods, including but not limited to gradient decent, the Karush-Kuhn-Tucker (KKT) conditions, Lagrangian duality, alternating direction method of multipliers (ADMM), and the kernel method. These methods are carefully applied to hard margin SVM, soft margin SVM, kernel PCA, ridge regression, lasso regression, and elastic-net regression. Matlab programs implementing these methods are included.
£162.00
World Scientific Publishing Co Pte Ltd Machine Learning: Concepts, Tools And Data
Book SynopsisThis set of lecture notes, written for those who are unfamiliar with mathematics and programming, introduces the reader to important concepts in the field of machine learning. It consists of three parts. The first is an overview of the history of artificial intelligence, machine learning, and data science, and also includes case studies of well-known AI systems. The second is a step-by-step introduction to Azure Machine Learning, with examples provided. The third is an explanation of the techniques and methods used in data visualization with R, which can be used to communicate the results collected by the AI systems when they are analyzed statistically. Practice questions are provided throughout the book.
£90.00
World Scientific Publishing Co Pte Ltd Machine Learning: Concepts, Tools And Data
Book SynopsisThis set of lecture notes, written for those who are unfamiliar with mathematics and programming, introduces the reader to important concepts in the field of machine learning. It consists of three parts. The first is an overview of the history of artificial intelligence, machine learning, and data science, and also includes case studies of well-known AI systems. The second is a step-by-step introduction to Azure Machine Learning, with examples provided. The third is an explanation of the techniques and methods used in data visualization with R, which can be used to communicate the results collected by the AI systems when they are analyzed statistically. Practice questions are provided throughout the book.
£42.75
World Scientific Publishing Co Pte Ltd Machine Learning - A Journey To Deep Learning:
Book SynopsisThis unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives — the statistical perspective, the artificial neural network perspective and the deep learning methodology.The useful reference text represents a solid foundation in machine learning and should prepare readers to apply and understand machine learning algorithms as well as to invent new machine learning methods. It tells a story outgoing from a perceptron to deep learning highlighted with concrete examples, including exercises and answers for the students.Related Link(s)
£139.50
World Scientific Publishing Co Pte Ltd Applied Software Development With Python &
Book SynopsisThe book presents the confluence of wearable and wireless inertial sensor systems, such as a smartphone, for deep brain stimulation for treating movement disorders, such as essential tremor, and machine learning. The machine learning distinguishes between distinct deep brain stimulation settings, such as 'On' and 'Off' status. This achievement demonstrates preliminary insight with respect to the concept of Network Centric Therapy, which essentially represents the Internet of Things for healthcare and the biomedical industry, inclusive of wearable and wireless inertial sensor systems, machine learning, and access to Cloud computing resources.Imperative to the realization of these objectives is the organization of the software development process. Requirements and pseudo code are derived, and software automation using Python for post-processing the inertial sensor signal data to a feature set for machine learning is progressively developed. A perspective of machine learning in terms of a conceptual basis and operational overview is provided. Subsequently, an assortment of machine learning algorithms is evaluated based on quantification of a reach and grasp task for essential tremor using a smartphone as a wearable and wireless accelerometer system.Furthermore, these skills regarding the software development process and machine learning applications with wearable and wireless inertial sensor systems enable new and novel biomedical research only bounded by the reader's creativity.Related Link(s)
£76.00
World Scientific Publishing Co Pte Ltd Clustering: Theoretical And Practical Aspects
Book SynopsisThis unique compendium gives an updated presentation of clustering, one of the most challenging tasks in machine learning. The book provides a unitary presentation of classical and contemporary algorithms ranging from partitional and hierarchical clustering up to density-based clustering, clustering of categorical data, and spectral clustering.Most of the mathematical background is provided in appendices, highlighting algebraic and complexity theory, in order to make this volume as self-contained as possible. A substantial number of exercises and supplements makes this a useful reference textbook for researchers and students.
£180.00
World Scientific Publishing Co Pte Ltd Handbook On Computer Learning And Intelligence
Book SynopsisThe Handbook on Computer Learning and Intelligence is a second edition which aims to be a one-stop-shop for the various aspects of the broad research area of computer learning and intelligence. This field of research evolved so much in the last five years that it necessitates this new edition of the earlier Handbook on Computational Intelligence.This two-volume handbook is divided into five parts. Volume 1 covers Explainable AI and Supervised Learning. Volume 2 covers three parts: Deep Learning, Intelligent Control, and Evolutionary Computation. The chapters detail the theory, methodology and applications of computer learning and intelligence, and are authored by some of the leading experts in the respective areas. The fifteen core chapters of the previous edition have been written and significantly refreshed by the same authors. Parts of the handbook have evolved to keep pace with the latest developments in computational intelligence in the areas that span across Machine Learning and Artificial Intelligence. The Handbook remains dedicated to applications and engineering-orientated aspects of these areas over abstract theories.Related Link(s)
£247.50
World Scientific Publishing Co Pte Ltd Signals, Instrumentation, Control, And Machine
Book SynopsisThis book stems from a unique and a highly effective approach to introducing signal processing, instrumentation, diagnostics, filtering, control, system integration, and machine learning.It presents the interactive industrial grade software testbed of mold oscillator that captures the distortion induced by beam resonance and uses this testbed as a virtual lab to generate input-output data records that permit unravelling complex system behavior, enhancing signal processing, modeling, and simulation background, and testing controller designs.All topics are presented in a visually rich and mathematically well supported, but not analytically overburdened format. By incorporating software testbed into homework and project assignments, the narrative guides a reader in an easily followed step-by-step fashion towards finding the mold oscillator disturbance removal solution currently used in the actual steel production, while covering the key signal processing, control, system integration, and machine learning concepts.The presentation is extensively class-tested and refined though the six-year usage of the book material in a required engineering course at the University of Illinois at Urbana-Champaign.
£162.00
World Scientific Publishing Co Pte Ltd Signals, Instrumentation, Control, And Machine
Book SynopsisThis book stems from a unique and a highly effective approach to introducing signal processing, instrumentation, diagnostics, filtering, control, system integration, and machine learning.It presents the interactive industrial grade software testbed of mold oscillator that captures the distortion induced by beam resonance and uses this testbed as a virtual lab to generate input-output data records that permit unravelling complex system behavior, enhancing signal processing, modeling, and simulation background, and testing controller designs.All topics are presented in a visually rich and mathematically well supported, but not analytically overburdened format. By incorporating software testbed into homework and project assignments, the narrative guides a reader in an easily followed step-by-step fashion towards finding the mold oscillator disturbance removal solution currently used in the actual steel production, while covering the key signal processing, control, system integration, and machine learning concepts.The presentation is extensively class-tested and refined though the six-year usage of the book material in a required engineering course at the University of Illinois at Urbana-Champaign.
£85.50
