Intelligent Systems And Machine Learning

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Building Intelligent Systems

Author : Geoff Hulten
Publisher : Apress
ISBN 13 : 1484234324
Total Pages : 346 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Building Intelligent Systems by : Geoff Hulten

Download or read book Building Intelligent Systems written by Geoff Hulten and published by Apress. This book was released on 2018-03-06 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Produce a fully functioning Intelligent System that leverages machine learning and data from user interactions to improve over time and achieve success. This book teaches you how to build an Intelligent System from end to end and leverage machine learning in practice. You will understand how to apply your existing skills in software engineering, data science, machine learning, management, and program management to produce working systems. Building Intelligent Systems is based on more than a decade of experience building Internet-scale Intelligent Systems that have hundreds of millions of user interactions per day in some of the largest and most important software systems in the world. What You’ll Learn Understand the concept of an Intelligent System: What it is good for, when you need one, and how to set it up for success Design an intelligent user experience: Produce data to help make the Intelligent System better over time Implement an Intelligent System: Execute, manage, and measure Intelligent Systems in practice Create intelligence: Use different approaches, including machine learning Orchestrate an Intelligent System: Bring the parts together throughout its life cycle and achieve the impact you want Who This Book Is For Software engineers, machine learning practitioners, and technical managers who want to build effective intelligent systems

Intelligent Systems for Engineers and Scientists

Author : Adrian A. Hopgood
Publisher : CRC Press
ISBN 13 : 1466516178
Total Pages : 455 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Intelligent Systems for Engineers and Scientists by : Adrian A. Hopgood

Download or read book Intelligent Systems for Engineers and Scientists written by Adrian A. Hopgood and published by CRC Press. This book was released on 2012-02-02 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: The third edition of this bestseller examines the principles of artificial intelligence and their application to engineering and science, as well as techniques for developing intelligent systems to solve practical problems. Covering the full spectrum of intelligent systems techniques, it incorporates knowledge-based systems, computational intelligence, and their hybrids. Using clear and concise language, Intelligent Systems for Engineers and Scientists, Third Edition features updates and improvements throughout all chapters. It includes expanded and separated chapters on genetic algorithms and single-candidate optimization techniques, while the chapter on neural networks now covers spiking networks and a range of recurrent networks. The book also provides extended coverage of fuzzy logic, including type-2 and fuzzy control systems. Example programs using rules and uncertainty are presented in an industry-standard format, so that you can run them yourself. The first part of the book describes key techniques of artificial intelligence—including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), frames, objects, agents, symbolic learning, case-based reasoning, genetic algorithms, optimization algorithms, neural networks, hybrids, and the Lisp and Prolog languages. The second part describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control. The author provides sufficient detail to help you develop your own intelligent systems for real applications. Whether you are building intelligent systems or you simply want to know more about them, this book provides you with detailed and up-to-date guidance. Check out the significantly expanded set of free web-based resources that support the book at: http://www.adrianhopgood.com/aitoolkit/

Intelligent Systems

Author : Crina Grosan
Publisher : Springer Science & Business Media
ISBN 13 : 364221004X
Total Pages : 450 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Intelligent Systems by : Crina Grosan

Download or read book Intelligent Systems written by Crina Grosan and published by Springer Science & Business Media. This book was released on 2011-07-29 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational intelligence is a well-established paradigm, where new theories with a sound biological understanding have been evolving. The current experimental systems have many of the characteristics of biological computers (brains in other words) and are beginning to be built to perform a variety of tasks that are difficult or impossible to do with conventional computers. As evident, the ultimate achievement in this field would be to mimic or exceed human cognitive capabilities including reasoning, recognition, creativity, emotions, understanding, learning and so on. This book comprising of 17 chapters offers a step-by-step introduction (in a chronological order) to the various modern computational intelligence tools used in practical problem solving. Staring with different search techniques including informed and uninformed search, heuristic search, minmax, alpha-beta pruning methods, evolutionary algorithms and swarm intelligent techniques; the authors illustrate the design of knowledge-based systems and advanced expert systems, which incorporate uncertainty and fuzziness. Machine learning algorithms including decision trees and artificial neural networks are presented and finally the fundamentals of hybrid intelligent systems are also depicted. Academics, scientists as well as engineers engaged in research, development and application of computational intelligence techniques, machine learning and data mining would find the comprehensive coverage of this book invaluable.

Intelligent Systems and Machine Learning for Industry

Author : P. R Anisha
Publisher : CRC Press
ISBN 13 : 1000828832
Total Pages : 362 pages
Book Rating : 4.0/5 (8 download)

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Book Synopsis Intelligent Systems and Machine Learning for Industry by : P. R Anisha

Download or read book Intelligent Systems and Machine Learning for Industry written by P. R Anisha and published by CRC Press. This book was released on 2022-12-21 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book explores the concepts and challenges in developing novel approaches using the Internet of Things, intelligent systems, machine intelligence systems, and data analytics in various industrial sectors such as manufacturing, smart agriculture, smart cities, food processing, environment, defense, stock market and healthcare. Further, it discusses the latest improvements in the industrial sectors using machine intelligence learning and intelligent systems techniques, especially robotics. Features: • Highlights case studies and solutions to industrial problems using machine learning and intelligent systems. • Covers applications in smart agriculture, smart healthcare, intelligent machines for disaster management, and smart manufacturing. • Provides the latest methodologies using machine intelligence systems in the early forecasting of weather. • Examines the research challenges and identifies the gaps in data collection and data analysis, especially imagery, signal, and speech. • Provides applications of digitization and smart processing using the Internet of Things and effective intelligent agent systems in manufacturing. • Discusses a systematic and exhaustive analysis of intelligent software effort estimation models. It will serve as an ideal reference text for graduate students, post-graduate students, IT Professionals, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

Machine Learning and IoT for Intelligent Systems and Smart Applications

Author : Madhumathy P
Publisher : CRC Press
ISBN 13 : 1000484963
Total Pages : 243 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Machine Learning and IoT for Intelligent Systems and Smart Applications by : Madhumathy P

Download or read book Machine Learning and IoT for Intelligent Systems and Smart Applications written by Madhumathy P and published by CRC Press. This book was released on 2021-11-17 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fusion of AI and IoT enables the systems to be predictive, prescriptive, and autonomous, and this convergence has evolved the nature of emerging applications from being assisted to augmented, and ultimately to autonomous intelligence. This book discusses algorithmic applications in the field of machine learning and IoT with pertinent applications. It further discusses challenges and future directions in the machine learning area and develops understanding of its role in technology, in terms of IoT security issues. Pertinent applications described include speech recognition, medical diagnosis, optimizations, predictions, and security aspects. Features: Focuses on algorithmic and practical parts of the artificial intelligence approaches in IoT applications. Discusses supervised and unsupervised machine learning for IoT data and devices. Presents an overview of the different algorithms related to Machine learning and IoT. Covers practical case studies on industrial and smart home automation. Includes implementation of AI from case studies in personal and industrial IoT. This book aims at Researchers and Graduate students in Computer Engineering, Networking Communications, Information Science Engineering, and Electrical Engineering.

Artificial Intelligence

Author : Michael Negnevitsky
Publisher : Pearson Education
ISBN 13 : 9780321204660
Total Pages : 454 pages
Book Rating : 4.2/5 (46 download)

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Book Synopsis Artificial Intelligence by : Michael Negnevitsky

Download or read book Artificial Intelligence written by Michael Negnevitsky and published by Pearson Education. This book was released on 2005 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Keeping the maths to a minimum, Negnevitsky explains the principles of AI, demonstrates how systems are built, what they are useful for and how to choose the right tool for the job.

Intelligent Systems: Theory, Research and Innovation in Applications

Author : Ricardo Jardim-Goncalves
Publisher : Springer Nature
ISBN 13 : 3030387046
Total Pages : 367 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Intelligent Systems: Theory, Research and Innovation in Applications by : Ricardo Jardim-Goncalves

Download or read book Intelligent Systems: Theory, Research and Innovation in Applications written by Ricardo Jardim-Goncalves and published by Springer Nature. This book was released on 2020-03-03 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: From artificial neural net / game theory / semantic applications, to modeling tools, smart manufacturing systems, and data science research – this book offers a broad overview of modern intelligent methods and applications of machine learning, evolutionary computation, Industry 4.0 technologies, and autonomous agents leading to the Internet of Things and potentially a new technological revolution. Though chiefly intended for IT professionals, it will also help a broad range of users of future emerging technologies adapt to the new smart / intelligent wave. In separate chapters, the book highlights fourteen successful examples of recent advances in the rapidly evolving area of intelligent systems. Covering major European projects paving the way to a serious smart / intelligent collaboration, the chapters explore e.g. cyber-security issues, 3D digitization, aerial robots, and SMEs that have introduced cyber-physical production systems. Taken together, they offer unique insights into contemporary artificial intelligence and its potential for innovation.

Machine Learning Paradigms

Author : Maria Virvou
Publisher : Springer
ISBN 13 : 3030137430
Total Pages : 223 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Machine Learning Paradigms by : Maria Virvou

Download or read book Machine Learning Paradigms written by Maria Virvou and published by Springer. This book was released on 2019-03-16 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent machine learning paradigms and advances in learning analytics, an emerging research discipline concerned with the collection, advanced processing, and extraction of useful information from both educators’ and learners’ data with the goal of improving education and learning systems. In this context, internationally respected researchers present various aspects of learning analytics and selected application areas, including: • Using learning analytics to measure student engagement, to quantify the learning experience and to facilitate self-regulation; • Using learning analytics to predict student performance; • Using learning analytics to create learning materials and educational courses; and • Using learning analytics as a tool to support learners and educators in synchronous and asynchronous eLearning. The book offers a valuable asset for professors, researchers, scientists, engineers and students of all disciplines. Extensive bibliographies at the end of each chapter guide readers to probe further into their application areas of interest.

Engineering Artificially Intelligent Systems

Author : William F. Lawless
Publisher : Springer Nature
ISBN 13 : 3030893855
Total Pages : 291 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Engineering Artificially Intelligent Systems by : William F. Lawless

Download or read book Engineering Artificially Intelligent Systems written by William F. Lawless and published by Springer Nature. This book was released on 2021-11-16 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many current AI and machine learning algorithms and data and information fusion processes attempt in software to estimate situations in our complex world of nested feedback loops. Such algorithms and processes must gracefully and efficiently adapt to technical challenges such as data quality induced by these loops, and interdependencies that vary in complexity, space, and time. To realize effective and efficient designs of computational systems, a Systems Engineering perspective may provide a framework for identifying the interrelationships and patterns of change between components rather than static snapshots. We must study cascading interdependencies through this perspective to understand their behavior and to successfully adopt complex system-of-systems in society. This book derives in part from the presentations given at the AAAI 2021 Spring Symposium session on Leveraging Systems Engineering to Realize Synergistic AI / Machine Learning Capabilities. Its 16 chapters offer an emphasis on pragmatic aspects and address topics in systems engineering; AI, machine learning, and reasoning; data and information fusion; intelligent systems; autonomous systems; interdependence and teamwork; human-computer interaction; trust; and resilience.

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

Author : Aurélien Géron
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 149203259X
Total Pages : 851 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by : Aurélien Géron

Download or read book Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow written by Aurélien Géron and published by "O'Reilly Media, Inc.". This book was released on 2019-09-05 with total page 851 pages. Available in PDF, EPUB and Kindle. Book excerpt: Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets

Intelligent Systems in Big Data, Semantic Web and Machine Learning

Author : Noreddine Gherabi
Publisher : Springer Nature
ISBN 13 : 303072588X
Total Pages : 315 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Intelligent Systems in Big Data, Semantic Web and Machine Learning by : Noreddine Gherabi

Download or read book Intelligent Systems in Big Data, Semantic Web and Machine Learning written by Noreddine Gherabi and published by Springer Nature. This book was released on 2021-05-28 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes important methodologies, tools and techniques from the fields of artificial intelligence, basically those which are based on relevant conceptual and formal development. The coverage is wide, ranging from machine learning to the use of data on the Semantic Web, with many new topics. The contributions are concerned with machine learning, big data, data processing in medicine, similarity processing in ontologies, semantic image analysis, as well as many applications including the use of machine leaning techniques for cloud security, artificial intelligence techniques for detecting COVID-19, the Internet of things, etc. The book is meant to be a very important and useful source of information for researchers and doctoral students in data analysis, Semantic Web, big data, machine learning, computer engineering and related disciplines, as well as for postgraduate students who want to integrate the doctoral cycle.

Introduction to Intelligent Systems in Traffic and Transportation

Author : Ana L.C. Rosenfeld
Publisher : Springer Nature
ISBN 13 : 3031015657
Total Pages : 119 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Introduction to Intelligent Systems in Traffic and Transportation by : Ana L.C. Rosenfeld

Download or read book Introduction to Intelligent Systems in Traffic and Transportation written by Ana L.C. Rosenfeld and published by Springer Nature. This book was released on 2022-05-31 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: Urban mobility is not only one of the pillars of modern economic systems, but also a key issue in the quest for equality of opportunity, once it can improve access to other services. Currently, however, there are a number of negative issues related to traffic, especially in mega-cities, such as economical issues (cost of opportunity caused by delays), environmental (externalities related to emissions of pollutants), and social (traffic accidents). Solutions to these issues are more and more closely tied to information and communication technology. Indeed, a search in the technical literature (using the keyword ``urban traffic" to filter out articles on data network traffic) retrieved the following number of articles (as of December 3, 2013): 9,443 (ACM Digital Library), 26,054 (Scopus), and 1,730,000 (Google Scholar). Moreover, articles listed in the ACM query relate to conferences as diverse as MobiCom, CHI, PADS, and AAMAS. This means that there is a big and diverse community of computer scientists and computer engineers who tackle research that is connected to the development of intelligent traffic and transportation systems. It is also possible to see that this community is growing, and that research projects are getting more and more interdisciplinary. To foster the cooperation among the involved communities, this book aims at giving a broad introduction into the basic but relevant concepts related to transportation systems, targeting researchers and practitioners from computer science and information technology. In addition, the second part of the book gives a panorama of some of the most exciting and newest technologies, originating in computer science and computer engineering, that are now being employed in projects related to car-to-car communication, interconnected vehicles, car navigation, platooning, crowd sensing and sensor networks, among others. This material will also be of interest to engineers and researchers from the traffic and transportation community.

Machine Learning and Artificial Intelligence

Author : A.J. Tallón-Ballesteros
Publisher : IOS Press
ISBN 13 : 1643681370
Total Pages : 482 pages
Book Rating : 4.6/5 (436 download)

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Book Synopsis Machine Learning and Artificial Intelligence by : A.J. Tallón-Ballesteros

Download or read book Machine Learning and Artificial Intelligence written by A.J. Tallón-Ballesteros and published by IOS Press. This book was released on 2020-12-15 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning and artificial intelligence are already widely applied to facilitate our daily lives, as well as scientific research, but with the world currently facing a global COVID-19 pandemic, their capacity to provide an important tool to support those searching for a way to combat the novel corona virus has never been more important. This book presents the proceedings of the International Conference on Machine Learning and Intelligent Systems (MLIS 2020), which was due to be held in Seoul, Korea, from 25-28 October 2020, but which was delivered as an online conference on the same dates due to COVID-19 restrictions. MLIS 2020 was the latest in a series of annual conferences that aim to provide a platform for exchanging knowledge about the most recent scientific and technological advances in the field of machine learning and intelligent systems. The annual conference also strengthens links within the scientific community in related research areas. The book contains 53 papers, selected from more than 160 submissions and presented at MLIS 2020. Selection was based on the results of review and scored on: originality, scientific/practical significance, compelling logical reasoning and language. Topics covered include: data mining, image processing, neural networks, human health, natural language processing, video processing, computational intelligence, expert systems, human-computer interaction, deep learning, and robotics. Offering a current overview of research and developments in machine learning and artificial intelligence, the book will be of interest to all those working in the field.

Intelligent Systems for Social Good

Author : Shyamapada Mukherjee
Publisher : Springer Nature
ISBN 13 : 9811907706
Total Pages : 212 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Intelligent Systems for Social Good by : Shyamapada Mukherjee

Download or read book Intelligent Systems for Social Good written by Shyamapada Mukherjee and published by Springer Nature. This book was released on 2022-06-11 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the connections between two technologies: artificial intelligence (AI) and Internet of things (IoT). It presents the application of these two technologies to solve various societal problems related to healthcare, agriculture, green environment, renewable energies, smart cities, etc. Each chapter in this book presents novel solutions to these problems along with the challenges in the application of AI and IoT to solve them. It discusses the adverse attacks on machine Learning models and how to protect sensitive data over the IoT networks. It also includes the security issues in IoT and their possible solutions.

Intelligent System Algorithms and Applications in Science and Technology

Author : Sunil Pathak
Publisher : CRC Press
ISBN 13 : 1000406873
Total Pages : 408 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Intelligent System Algorithms and Applications in Science and Technology by : Sunil Pathak

Download or read book Intelligent System Algorithms and Applications in Science and Technology written by Sunil Pathak and published by CRC Press. This book was released on 2022-02-03 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 21st century has witnessed massive changes around the world in intelligence systems in order to become smarter, energy efficient, reliable, and cheaper. This volume explores the application of intelligent techniques in various fields of engineering and technology. It addresses diverse topics in such areas as machine learning-based intelligent systems for healthcare, applications of artificial intelligence and the Internet of Things, intelligent data analytics techniques, intelligent network systems and applications, and inequalities and process control systems. The authors explore the full breadth of the field, which encompasses data analysis, image processing, speech processing and recognition, medical science and healthcare monitoring, smart irrigation systems, insurance and banking, robotics and process control, and more.

Modelling and Development of Intelligent Systems

Author : Dana Simian
Publisher : Springer Nature
ISBN 13 : 3030685276
Total Pages : 411 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Modelling and Development of Intelligent Systems by : Dana Simian

Download or read book Modelling and Development of Intelligent Systems written by Dana Simian and published by Springer Nature. This book was released on 2021-02-12 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed proceedings of the 7th International Conference on Modelling and Development of Intelligent Systems, MDIS 2020, held in Sibiu, Romania, in October 2020. Due to the COVID-19 pandemic the conference was held online. The 25 revised full papers presented in the volume were carefully reviewed and selected from 57 submissions. The papers are organized in topical sections on evolutionary computing; intelligent systems for decision support; machine learning; mathematical models for development of intelligent systems; modelling and optimization of dynamic systems; ontology engineering.

Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems

Author : Uddin, M. Irfan
Publisher : IGI Global
ISBN 13 :
Total Pages : 307 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems by : Uddin, M. Irfan

Download or read book Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems written by Uddin, M. Irfan and published by IGI Global. This book was released on 2024-02-26 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: The applications of rapidly advancing intelligent systems are so varied that many are still yet to be discovered. There is often a disconnect between experts in computer science, artificial intelligence, machine learning, robotics, and other specialties, which inhibits the potential for the expansion of this technology and its many benefits. A resource that encourages interdisciplinary collaboration is needed to bridge the gap between these respected leaders of their own fields. Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems represents an exploration of the forefront of artificial intelligence, navigating the complexities of this field and its many applications. This guide expertly navigates through the intricate domains of deep learning and reinforcement learning, offering an in-depth journey through foundational principles, advanced methodologies, and cutting-edge algorithms shaping the trajectory of intelligent systems. The book covers an introduction to artificial intelligence and its subfields, foundational aspects of deep learning, a demystification of the architecture of neural networks, the mechanics of backpropagation, and the intricacies of critical elements such as activation and loss functions. The book serves as a valuable educational resource for professionals. Its structured approach makes it an ideal reference for students, researchers, and industry professionals.