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pIntroduction.- Introduction to AI and ML.- Essential Concepts in Artificial Intelligence and Machine Learning.- Data Understanding, Representation, and Visualization.- Linear Methods.- Perceptron and Neural Networks.- Decision Trees.- Support Vector Machines.- Probabilistic Models.- Dynamic Programming and Reinforcement Learning.- Evolutionary Algorithms.- Time Series Models.- Deep Learning.- Emerging Trends in Machine Learning.- Unsupervised Learning.- Featurization.- Designing and Tuning.- Model Pipelines.- Performance Measurement.- Classification.- Regression.- Ranking.- Recommendations Systems.- Azure Machine Learning.- Open Source Machine Learning Libraries.- Amazon's Machine Learning Toolkit Sagemaker.- Conclusion.ppp

Machine Learning and Artificial Intelligence | Joshi Ameet V. | Twarda | Twarda

AI-Powered IoT in the Energy Industry Digital Technology and Sustainable Energy Systems looks at opportunities to employ cutting-edge applications of artificial intelligence AI, the Internet of Things IoT, and Machine Learning ML in designing and modeling energy and renewable energy systems.

AI | Powered Iot in the Energy Industry | Vijayalakshmi S. | Twarda

This book presents research related to smart devices and Internet of Things IoT that are intended to advance environmental sustainability. With sustainability as the focus, the topics covered include designing and controlling of smart systems, networking and machine learning, monitoring and controlling the environment, smart metering, authentication and authorization, and software and systems solution. The authors discuss how IoT can aid in sustainability through its implementation of systems interconnecting several objects, whether in the physical or in the virtual worlds. The chapters also present several applications including in smart homes, transportation, and healthcare. The book pertains to researchers, academics, and professionals.pp

Iot and Smart Devices for Sustainable Environment | Azrour Mourade | Twarda | Twarda

User experience UX design practices have seen a fundamental shift as more and more software products incorporate machine learning ML components and artificial intelligence AI algorithms at their core. This book will probe into UX design's role in making technologies inclusive and enabling user collaboration with AI. brAIML-based systems have changed the way of traditional UX design. Instead of programming a method to do a specific action, creators of these systems provide data and nurture them to curate outcomes based on inputs. These systems are dynamic and while AI systems change over time, their user experience, in many cases, does not adapt to this dynamic nature. brApplied UX Design for Artificial Intelligence will explore this problem, addressing the challenges and opportunities in UX design for AIML systems, look at best practices for designers, managers, and product creators and showcase how individuals from a non-technical background can collaborate effectively with AI and Mac

Designing Human | Centric AI Experiences | Kore Akshay | Twarda

pbiIntelligent Computing for Interactive System Design provides a comprehensive resource on what has become the dominant paradigm in designing novel interaction methods, involving gestures, speech, text, touch and brain-controlled interaction, embedded in innovative and emerging human-computer interfaces.bi These interfaces support ubiquitous interaction with applications and services running on smartphones, wearables, in-vehicle systems, virtual and augmented reality, robotic systems, the Internet of Things IoT, and many other domains that are now highly competitive, both in commercial and in research contexts.p pThis book presents the crucial theoretical foundations needed by any student, researcher, or practitioner working on novel interface design, with chapters on statistical methods, digital signal processing DSP, and machine learning ML. These foundations are followed by chapters that discuss case studies on smart cities, brain-computer interfaces, probabilistic mobile text entr

Intelligent Computing for Interactive System Design | Eslambolchilar Parisa | Twarda

piAI-Powered IoT in the Energy Industry Digital Technology and Sustainable Energy Systemsi looks at opportunities to employ cutting-edge applications of artificial intelligence AI, the Internet of Things IoT, and Machine Learning ML in designing and modeling energy and renewable energy systems. The book's main objectives are to demonstrate how big data can help with energy efficiency and demand reduction, increase the usage of renewable energy sources, and assist in transitioning from a centralized system to a distributed, efficient, and embedded energy system. Contributions cover the fundamentals of the renewable energy sector, including solar, wind, biomass, and hydrogen, as well as building services and power generation systems. Chapters also examine renewable energy property prediction methods and discuss AI and IoT prediction models for biomass thermal properties.pulli8203Covers renewable energy sector fundamentalsliliExplains the application of big data in distributed energy doma

Data science has been playing a vital role in almost all major fields. Many researchers are interested in the development of IT applications, which are user-driven with a focus on issues. This can be addressed using data science. User-driven research and data science have gained much attention from many private, public, and government organizations and research institutions. Designing User Interfaces With a Data Science Approach promotes the inclusion of more diversified users for user-centered designs of applications across domains and analyzes user data with a data science approach for effective and user-friendly user interface designs. It introduces the foundations of advanced topics of human-computer interaction, particularly with user-centered designs and techniques. Covering topics such as artificial neural networks, natural dialog systems, and machine learning, this book is an essential resource for faculty, research scholars, industry professionals, students of higher education

Designing User Interfaces With a Data Science Approach | Banubakode Abhijit Narayanrao | Paperback | Twarda

bDRUG DESIGN USING MACHINE LEARNINGb pbThe use of machine learning algorithms in drug discovery has accelerated in recent years and this book provides an in-depth overview of the still-evolving field.b pThe objective of this book is to bring together several chapters that function as an overview of the use of machine learning and artificial intelligence applied to drug development. The initial chapters discuss drug-target interactions through machine learning for improving drug delivery, healthcare, and medical systems. Further chapters also provide topics on drug repurposing through machine learning, drug designing, and ultimately discuss drug combinations prescribed for patients with multiple or complex ailments. pThis excellent overview ulliProvides a broad synopsis of machine learning and artificial intelligence applications to the advancement of drugsli liDetails the use of molecular recognition for drug development through various mathematical modelsli liHighlights classical as w

Drug Design Using Machine Learning | Inamuddin | Twarda | Twarda

Written by leading researchers, this complete introduction brings together all the theory and tools needed for building robust machine learning in adversarial environments. Discover how machine learning systems can adapt when an adversary actively poisons data to manipulate statistical inference, learn the latest practical techniques for investigating system security and performing robust data analysis, and gain insight into new approaches for designing effective countermeasures against the latest wave of cyber-attacks. Privacy-preserving mechanisms and the near-optimal evasion of classifiers are discussed in detail, and in-depth case studies on email spam and network security highlight successful attacks on traditional machine learning algorithms. Providing a thorough overview of the current state of the art in the field, and possible future directions, this groundbreaking work is essential reading for researchers, practitioners and students in computer security and machine learning, 

Adversarial Machine Learning | Joseph Anthony D. | Twarda | Twarda

pThere is no strict definition of unconventional computing. Being an unconventional computist is not a matter of training but thinking and living. Phenomenologically most works on unconventional computing are about implementation of computing in novel substrates chemical, physical, biological, development of computing schemes and algorithms not fitting into the mainstream framework, or designing of computing architectures inspired by chemical or biological systems. This short book gives a snapshot of the unconventional computing field. The world-leading experts in the unconventional computing author all articles of the issue. The topics include analog computation, sensing and computing with fungi, chemical computing, swarms of minimalist agents, computational universality, mega-computing in the universe, information and music, universal sensing, art of deduction, reversible computing, philosophy of machine learning, epistemic incompleteness, post-quantum unconventional computing, compl

Thoughts on unconventional computing | Adamatzky Andrew | Paperback | Twarda

pstrongLeverage top XAI frameworks to explain your machine learning models with ease and discover best practices and guidelines to build scalable explainable ML systemsstrongppbrppstrongKey Features strongpulliExplore various explainability methods for designing robust and scalable explainable ML systemsliliUse XAI frameworks such as LIME and SHAP to make ML models explainable to solve practical problemsliliDesign user-centric explainable ML systems using guidelines provided for industrial applicationsliulpbrppstrongBook Description strongppExplainable AI XAI is an emerging field that brings artificial intelligence AI closer to non-technical end users. XAI makes machine learning ML models transparent and trustworthy along with promoting AI adoption for industrial and research use cases.ppApplied Machine Learning Explainability Techniques comes with a unique blend of industrial and academic research perspectives to help you acquire practical XAI skills. You'll begin by gaining a concept

Applied Machine Learning Explainability Techniques | Bhattacharya Aditya | Twarda

pThe concepts of telemedicine and e-healthcare have eased as well as improved the reachability of experienced doctors and medical staff to remote patients. A patient who is living in a remote village area can directly connect to specialist doctors across the globe though hisher mobile phone using telemedicine systems and e-healthcare services.ppIn pandemic situations like COVID-19, these online platforms helped society to get medical treatment from their residence without any physical movement. Technology is transforming human lives by playing an important role in the planning, designing, and development of intelligent systems for better service.ppThis book presents a cross-disciplinary perspective on the concept of machine learning, blockchain and IoT by congregating cutting-edge research and insights. It also identifies and discusses various advanced technologies such as internet of things IoT, big data analytics, machine learning, artificial intelligence, cyber security, cloud compu

Artificial Intelligence, Blockchain and IoT for Smart Healthcare | Sharma Hitesh Kumar | Twarda | Twarda

pImplementing and designing systems that make suggestions to users are among the most popular and essential machine learning applications available. Whether you want customers to find the most appealing items at your online store, videos to enrich and entertain them, or news they need to know, recommendation systems RecSys provide the way. p In this practical book, authors Bryan Bischof and Hector Yee illustrate the core concepts and examples to help you create a RecSys for any industry or scale. You'll learn the math, ideas, and implementation details you need to succeed. This book includes the RecSys platform components, relevant MLOps tools in your stack, plus code examples and helpful suggestions in PySpark, SparkSQL, FastAPI, Weights  Biases, and Kafka. p You'll learn ul liThe data essential for building a RecSys liHow to frame your data and business as a RecSys problem liWays to evaluate models appropriate for your system liMethods to implement, train, test, and deploy the model 

Building Recommendation Systems in Python and Jax | Bischof Bryan | Twarda

pOffering a holistic view of the pioneering trends and innovations in Smart Healthcare Management, this book focuses on the methodologies, frameworks, design issues, tools, architectures, and technologies necessary to develop and understand intelligent healthcare systems and emerging applications in the present era.ppiSmart Technologies in Healthcare Management Pioneering Trends and Applicationsi provides an overview of various technical and innovative aspects, challenges, and issues in smart healthcare, along with recent and novel findings. It highlights the latest advancements and applications in the field of intelligent systems and explores the importance of cloud computing and the designing of sensors in an IoT system. The book offers algorithms and a framework with models in Machine Learning and AI for Smart Healthcare Management. A detailed flow chart and innovative and modified methodologies related to intelligent computing in healthcare are discussed, as well as real-world-base

Smart Technologies in Healthcare Management | Sindhwani Nidhi | Twarda

pThis new volume explores a variety of modern techniques that deal with estimated models and give resolutions to complex real-life issues. Soft computing has played a crucial role not only with theoretical paradigms but is also popular for its pivotal role for designing a large variety of expert systems and artificial intelligence-based applications.ppInvolving the concepts and practices of soft computing in conjunction with other frontier research domains, this book begins with the basics and goes on to explore a variety of modern applications of soft computing in areas such as approximate reasoning, artificial neural networks, Bayesian networks, big data analytics, bioinformatics, cloud computing, control systems, data mining, functional approximation, fuzzy logic, genetic and evolutionary algorithms, hybrid models, machine learning, metaheuristics, neuro fuzzy system, optimization, randomized searches, and swarm intelligence.ppThis book will be helpful to a wide range of readers who

Applied Soft Computing | Borah Samarjeet | Twarda

Information geometry refers to an interdisciplinary field that studies statistics and probability theory by applying the techniques of differential geometry. It investigates statistical manifolds, which are Riemannian manifolds, where each point is a probability distribution. Information geometry offers a differential-geometric structure on manifolds that help in designing and studying statistical decision rules. It has been utilized in a variety of applications such as machine learning, quantum systems, mathematical finance, statistical inference, and neural networks. The amount of information integration within various terminals of a causal dynamical system is measured using information geometry. The amount of information lost can be measured using integrated information when a system is divided into parts and information transmission between the parts is stopped. This book provides comprehensive insights into information geometry and its applications. It presents researches and stud

Information Geometry and Its Applications | Cox Brayan | Twarda | Twarda

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designing machine learning systems