Artificial Intelligence Algorithms And Applications

Author : Mettu Srinivas,G. Sucharitha,Anjanna Matta
Publisher : John Wiley & Sons
Page : 372 pages
File Size : 40,8 Mb
Release : 2021-08-10
Category : Computers
ISBN : 9781119769248

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Machine Learning Algorithms and Applications by Mettu Srinivas,G. Sucharitha,Anjanna Matta Pdf

Machine Learning Algorithms is for current and ambitious machine learning specialists looking to implement solutions to real-world machine learning problems. It talks entirely about the various applications of machine and deep learning techniques, with each chapter dealing with a novel approach of machine learning architecture for a specific application, and then compares the results with previous algorithms. The book discusses many methods based in different fields, including statistics, pattern recognition, neural networks, artificial intelligence, sentiment analysis, control, and data mining, in order to present a unified treatment of machine learning problems and solutions. All learning algorithms are explained so that the user can easily move from the equations in the book to a computer program.

Author : Terje Solsvik Kristensen
Publisher : Bentham Science Publishers
Page : 176 pages
File Size : 48,6 Mb
Release : 2021-05-31
Category : Computers
ISBN : 9781681088273

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Artificial Intelligence: Models, Algorithms and Applications by Terje Solsvik Kristensen Pdf

Artificial Intelligence: Models, Algorithms and Applications presents focused information about applications of artificial intelligence (AI) in different areas to solve complex problems. The book presents 8 chapters that demonstrate AI based systems for vessel tracking, mental health assessment, radiology, instrumentation, business intelligence, education and criminology. The book concludes with a chapter on mathematical models of neural networks. The book serves as an introductory book about AI applications at undergraduate and graduate levels and as a reference for industry professionals working with AI based systems.

Author : Ricardo López-Ruiz
Publisher : Unknown
Page : 218 pages
File Size : 50,9 Mb
Release : 2018
Category : Algorithms
ISBN : 9781789847024

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From Natural to Artificial Intelligence by Ricardo López-Ruiz Pdf

Author : Santosh Kumar Das,Shom Prasad Das,Nilanjan Dey,Aboul-Ella Hassanien
Publisher : Springer Nature
Page : 321 pages
File Size : 43,7 Mb
Release : 2020-07-18
Category : Technology & Engineering
ISBN : 9783030506414

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Machine Learning Algorithms for Industrial Applications by Santosh Kumar Das,Shom Prasad Das,Nilanjan Dey,Aboul-Ella Hassanien Pdf

This book explores several problems and their solutions regarding data analysis and prediction for industrial applications. Machine learning is a prominent topic in modern industries: its influence can be felt in many aspects of everyday life, as the world rapidly embraces big data and data analytics. Accordingly, there is a pressing need for novel and innovative algorithms to help us find effective solutions in industrial application areas such as media, healthcare, travel, finance, and retail. In all of these areas, data is the crucial parameter, and the main key to unlocking the value of industry. The book presents a range of intelligent algorithms that can be used to filter useful information in the above-mentioned application areas and efficiently solve particular problems. Its main objective is to raise awareness for this important field among students, researchers, and industrial practitioners.

Author : Uday Shankar,Andreas Spanias
Publisher : Springer Nature
Page : 107 pages
File Size : 53,9 Mb
Release : 2022-05-31
Category : Technology & Engineering
ISBN : 9783031037580

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Machine and Deep Learning Algorithms and Applications by Uday Shankar,Andreas Spanias Pdf

This book introduces basic machine learning concepts and applications for a broad audience that includes students, faculty, and industry practitioners. We begin by describing how machine learning provides capabilities to computers and embedded systems to learn from data. A typical machine learning algorithm involves training, and generally the performance of a machine learning model improves with more training data. Deep learning is a sub-area of machine learning that involves extensive use of layers of artificial neural networks typically trained on massive amounts of data. Machine and deep learning methods are often used in contemporary data science tasks to address the growing data sets and detect, cluster, and classify data patterns. Although machine learning commercial interest has grown relatively recently, the roots of machine learning go back to decades ago. We note that nearly all organizations, including industry, government, defense, and health, are using machine learning to address a variety of needs and applications. The machine learning paradigms presented can be broadly divided into the following three categories: supervised learning, unsupervised learning, and semi-supervised learning. Supervised learning algorithms focus on learning a mapping function, and they are trained with supervision on labeled data. Supervised learning is further sub-divided into classification and regression algorithms. Unsupervised learning typically does not have access to ground truth, and often the goal is to learn or uncover the hidden pattern in the data. Through semi-supervised learning, one can effectively utilize a large volume of unlabeled data and a limited amount of labeled data to improve machine learning model performances. Deep learning and neural networks are also covered in this book. Deep neural networks have attracted a lot of interest during the last ten years due to the availability of graphics processing units (GPU) computational power, big data, and new software platforms. They have strong capabilities in terms of learning complex mapping functions for different types of data. We organize the book as follows. The book starts by introducing concepts in supervised, unsupervised, and semi-supervised learning. Several algorithms and their inner workings are presented within these three categories. We then continue with a brief introduction to artificial neural network algorithms and their properties. In addition, we cover an array of applications and provide extensive bibliography. The book ends with a summary of the key machine learning concepts.

Author : Zoltán Somogyi
Publisher : Springer Nature
Page : 448 pages
File Size : 43,8 Mb
Release : 2021-03-11
Category : Computers
ISBN : 9783030600327

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The Application of Artificial Intelligence by Zoltán Somogyi Pdf

This book presents a unique, understandable view of machine learning using many practical examples and access to free professional software and open source code. The user-friendly software can immediately be used to apply everything you learn in the book without the need for programming. After an introduction to machine learning and artificial intelligence, the chapters in Part II present deeper explanations of machine learning algorithms, performance evaluation of machine learning models, and how to consider data in machine learning environments. In Part III the author explains automatic speech recognition, and in Part IV biometrics recognition, face- and speaker-recognition. By Part V the author can then explain machine learning by example, he offers cases from real-world applications, problems, and techniques, such as anomaly detection and root cause analyses, business process improvement, detecting and predicting diseases, recommendation AI, several engineering applications, predictive maintenance, automatically classifying datasets, dimensionality reduction, and image recognition. Finally, in Part VI he offers a detailed explanation of the AI-TOOLKIT, software he developed that allows the reader to test and study the examples in the book and the application of machine learning in professional environments. The author introduces core machine learning concepts and supports these with practical examples of their use, so professionals will appreciate his approach and use the book for self-study. It will also be useful as a supplementary resource for advanced undergraduate and graduate courses on machine learning and artificial intelligence.

Author : Kangshun Li,Wei Li,Hui Wang,Yong Liu
Publisher : Springer Nature
Page : 811 pages
File Size : 51,7 Mb
Release : 2020-05-25
Category : Computers
ISBN : 9789811555770

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Artificial Intelligence Algorithms and Applications by Kangshun Li,Wei Li,Hui Wang,Yong Liu Pdf

This book constitutes the thoroughly refereed proceedings of the 11th International Symposium on Intelligence Computation and Applications, ISICA 2019, held in Guangzhou, China, in November 2019. The 65 papers presented were carefully reviewed and selected from the total of 112 submissions. This volume features the most up-to-date research in evolutionary algorithms, parallel computing and quantum computing, evolutionary multi-objective and dynamic optimization, intelligent multimedia systems, virtualization and AI applications, smart scheduling, intelligent control, big data and cloud computing, deep learning, and hybrid machine learning systems.The papers are organized according to the following topical sections: new frontier in evolutionary algorithms; evolutionary multi-objective and dynamic optimization; intelligent multimedia systems; virtualization and AI applications; smart scheduling; intelligent control; big data and cloud computing; statistical learning.

Author : Mohssen Mohammed,Muhammad Badruddin Khan,Eihab Bashier Mohammed Bashier
Publisher : CRC Press
Page : 227 pages
File Size : 50,8 Mb
Release : 2016-08-19
Category : Computers
ISBN : 9781498705394

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Machine Learning by Mohssen Mohammed,Muhammad Badruddin Khan,Eihab Bashier Mohammed Bashier Pdf

Machine learning, one of the top emerging sciences, has an extremely broad range of applications. However, many books on the subject provide only a theoretical approach, making it difficult for a newcomer to grasp the subject material. This book provides a more practical approach by explaining the concepts of machine learning algorithms and describing the areas of application for each algorithm, using simple practical examples to demonstrate each algorithm and showing how different issues related to these algorithms are applied.

Author : Rishal Hurbans
Publisher : Simon and Schuster
Page : 392 pages
File Size : 45,6 Mb
Release : 2020-07-20
Category : Computers
ISBN : 9781638355687

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Grokking Artificial Intelligence Algorithms by Rishal Hurbans Pdf

"From start to finish, the best book to help you learn AI algorithms and recall why and how you use them." - Linda Ristevski, York Region District School Board ”This book takes an impossibly broad area of computer science and communicates what working developers need to understand in a clear and thorough way.” - David Jacobs, Product Advance Local Key Features Master the core algorithms of deep learning and AI Build an intuitive understanding of AI problems and solutions Written in simple language, with lots of illustrations and hands-on examples Creative coding exercises, including building a maze puzzle game and exploring drone optimization About The Book “Artificial intelligence” requires teaching a computer how to approach different types of problems in a systematic way. The core of AI is the algorithms that the system uses to do things like identifying objects in an image, interpreting the meaning of text, or looking for patterns in data to spot fraud and other anomalies. Mastering the core algorithms for search, image recognition, and other common tasks is essential to building good AI applications Grokking Artificial Intelligence Algorithms uses illustrations, exercises, and jargon-free explanations to teach fundamental AI concepts.You’ll explore coding challenges like detect­ing bank fraud, creating artistic masterpieces, and setting a self-driving car in motion. All you need is the algebra you remember from high school math class and beginning programming skills. What You Will Learn Use cases for different AI algorithms Intelligent search for decision making Biologically inspired algorithms Machine learning and neural networks Reinforcement learning to build a better robot This Book Is Written For For software developers with high school–level math skills. About the Author Rishal Hurbans is a technologist, startup and AI group founder, and international speaker. Table of Contents 1 Intuition of artificial intelligence 2 Search fundamentals 3 Intelligent search 4 Evolutionary algorithms 5 Advanced evolutionary approaches 6 Swarm intelligence: Ants 7 Swarm intelligence: Particles 8 Machine learning 9 Artificial neural networks 10 Reinforcement learning with Q-learning

Author : Jingzheng Ren,Weifeng Shen,Yi Man,Lichun Dong
Publisher : Elsevier
Page : 542 pages
File Size : 54,8 Mb
Release : 2021-06-05
Category : Technology & Engineering
ISBN : 9780128217436

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Applications of Artificial Intelligence in Process Systems Engineering by Jingzheng Ren,Weifeng Shen,Yi Man,Lichun Dong Pdf

Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis Gives direction to future development trends of AI technologies in chemical and process engineering

Author : Anonim
Publisher : BoD – Books on Demand
Page : 153 pages
File Size : 54,6 Mb
Release : 2021-12-22
Category : Computers
ISBN : 9781839694844

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Machine Learning by Anonim Pdf

Recent times are witnessing rapid development in machine learning algorithm systems, especially in reinforcement learning, natural language processing, computer and robot vision, image processing, speech, and emotional processing and understanding. In tune with the increasing importance and relevance of machine learning models, algorithms, and their applications, and with the emergence of more innovative uses–cases of deep learning and artificial intelligence, the current volume presents a few innovative research works and their applications in real-world, such as stock trading, medical and healthcare systems, and software automation. The chapters in the book illustrate how machine learning and deep learning algorithms and models are designed, optimized, and deployed. The volume will be useful for advanced graduate and doctoral students, researchers, faculty members of universities, practicing data scientists and data engineers, professionals, and consultants working on the broad areas of machine learning, deep learning, and artificial intelligence.

Author : Ricardo Lopez-Ruiz
Publisher : Unknown
Page : 216 pages
File Size : 54,6 Mb
Release : 2018
Category : Electronic computers. Computer science
ISBN : 1789847036

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From Natural to Artificial Intelligence - Algorithms and Applications by Ricardo Lopez-Ruiz Pdf

Artificial intelligence (AI) is a field experiencing constant growth and change, with a long history. The challenge to reproduce human behavior in machines requires the interaction of many fields, from engineering to mathematics, from neurology to biology, from computer science to robotics, from web search to social networks, from machine learning to game theory, etc. Numerous applications and possibilities of AI are already a reality but other ones are still needed to reduce the human limitations and to expand the human capability to limits beyond our imagination. This book brings together researchers working on areas related to AI such as speech and face recognition, representation of learning and acoustic scenarios, fuzzy inference and data exploration, cellular automata applications with a special interest in the tools and algorithms that can be applied in these different branches of the AI discipline. The book provides a new reference to an audience interested in the development of this field.

Author : Rajesh Jha,Bimal Kumar Jha
Publisher : CRC Press
Page : 363 pages
File Size : 41,7 Mb
Release : 2022-03-15
Category : Technology & Engineering
ISBN : 9781000541335

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Artificial Intelligence-Aided Materials Design by Rajesh Jha,Bimal Kumar Jha Pdf

This book describes the application of artificial intelligence (AI)/machine learning (ML) concepts to develop predictive models that can be used to design alloy materials, including hard and soft magnetic alloys, nickel-base superalloys, titanium-base alloys, and aluminum-base alloys. Readers new to AI/ML algorithms can use this book as a starting point and use the MATLAB® and Python implementation of AI/ML algorithms through included case studies. Experienced AI/ML researchers who want to try new algorithms can use this book and study the case studies for reference. Offers advantages and limitations of several AI concepts and their proper implementation in various data types generated through experiments and computer simulations and from industries in different file formats Helps readers to develop predictive models through AI/ML algorithms by writing their own computer code or using resources where they do not have to write code Covers downloadable resources such as MATLAB GUI/APP and Python implementation that can be used on common mobile devices Discusses the CALPHAD approach and ways to use data generated from it Features a chapter on metallurgical/materials concepts to help readers understand the case studies and thus proper implementation of AI/ML algorithms under the framework of data-driven materials science Uses case studies to examine the importance of using unsupervised machine learning algorithms in determining patterns in datasets This book is written for materials scientists and metallurgists interested in the application of AI, ML, and data science in the development of new materials.

Author : Sunil Pathak,Pramod Kumar Bhatt,Sanjay Kumar Singh,Ashutosh Tripathi,Pankaj Kumar Pandey
Publisher : CRC Press
Page : 408 pages
File Size : 45,6 Mb
Release : 2022-02-03
Category : Computers
ISBN : 9781000406870

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Intelligent System Algorithms and Applications in Science and Technology by Sunil Pathak,Pramod Kumar Bhatt,Sanjay Kumar Singh,Ashutosh Tripathi,Pankaj Kumar Pandey Pdf

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.

Author : Vasant, Pandian
Publisher : IGI Global
Page : 873 pages
File Size : 54,5 Mb
Release : 2014-11-30
Category : Computers
ISBN : 9781466672598

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Handbook of Research on Artificial Intelligence Techniques and Algorithms by Vasant, Pandian Pdf

For decades, optimization methods such as Fuzzy Logic, Artificial Neural Networks, Firefly, Simulated annealing, and Tabu search, have been capable of handling and tackling a wide range of real-world application problems in society and nature. Analysts have turned to these problem-solving techniques in the event during natural disasters and chaotic systems research. The Handbook of Research on Artificial Intelligence Techniques and Algorithms highlights the cutting edge developments in this promising research area. This premier reference work applies Meta-heuristics Optimization (MO) Techniques to real world problems in a variety of fields including business, logistics, computer science, engineering, and government. This work is particularly relevant to researchers, scientists, decision-makers, managers, and practitioners.