Applications Of Artificial Intelligence And Neural Systems To Data Science
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Applications Of Artificial Intelligence And Neural Systems To Data Science
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Author : Anna Esposito
language : en
Publisher: Springer Nature
Release Date : 2023-09-02
Applications Of Artificial Intelligence And Neural Systems To Data Science written by Anna Esposito and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-02 with Technology & Engineering categories.
This book provides an overview on the current progresses in artificial intelligence and neural nets in data science. The book is reporting on intelligent algorithms and applications modeling, prediction, and recognition tasks and many other application areas supporting complex multimodal systems to enhance and improve human–machine or human–human interactions. This field is broadly addressed by the scientific communities and has a strong commercial impact since investigates on the theoretical frameworks supporting the implementation of sophisticated computational intelligence tools. Such tools will support multidisciplinary aspects of data mining and data processing characterizing appropriate system reactions to human-machine interactional exchanges in interactive scenarios. The emotional issue has recently gained increasing attention for such complex systems due to its relevance in helping in the most common human tasks (like cognitive processes, perception, learning, communication, and even "rational" decision-making) and therefore improving the quality of life of the end users.
Biomedical And Business Applications Using Artificial Neural Networks And Machine Learning
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Author : Segall, Richard S.
language : en
Publisher: IGI Global
Release Date : 2022-01-07
Biomedical And Business Applications Using Artificial Neural Networks And Machine Learning written by Segall, Richard S. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-07 with Computers categories.
During these uncertain and turbulent times, intelligent technologies including artificial neural networks (ANN) and machine learning (ML) have played an incredible role in being able to predict, analyze, and navigate unprecedented circumstances across a number of industries, ranging from healthcare to hospitality. Multi-factor prediction in particular has been especially helpful in dealing with the most current pressing issues such as COVID-19 prediction, pneumonia detection, cardiovascular diagnosis and disease management, automobile accident prediction, and vacation rental listing analysis. To date, there has not been much research content readily available in these areas, especially content written extensively from a user perspective. Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning is designed to cover a brief and focused range of essential topics in the field with perspectives, models, and first-hand experiences shared by prominent researchers, discussing applications of artificial neural networks (ANN) and machine learning (ML) for biomedical and business applications and a listing of current open-source software for neural networks, machine learning, and artificial intelligence. It also presents summaries of currently available open source software that utilize neural networks and machine learning. The book is ideal for professionals, researchers, students, and practitioners who want to more fully understand in a brief and concise format the realm and technologies of artificial neural networks (ANN) and machine learning (ML) and how they have been used for prediction of multi-disciplinary research problems in a multitude of disciplines.
Applications Of Artificial Neural Networks For Nonlinear Data
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Author : Patel, Hiral Ashil
language : en
Publisher: IGI Global
Release Date : 2020-09-25
Applications Of Artificial Neural Networks For Nonlinear Data written by Patel, Hiral Ashil and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-25 with Computers categories.
Processing information and analyzing data efficiently and effectively is crucial for any company that wishes to stay competitive in its respective market. Nonlinear data presents new challenges to organizations, however, due to its complexity and unpredictability. The only technology that can properly handle this form of data is artificial neural networks. These modeling systems present a high level of benefits in analyzing complex data in a proficient manner, yet considerable research on the specific applications of these intelligent components is significantly deficient. Applications of Artificial Neural Networks for Nonlinear Data is a collection of innovative research on the contemporary nature of artificial neural networks and their specific implementations within data analysis. While highlighting topics including propagation functions, optimization techniques, and learning methodologies, this book is ideally designed for researchers, statisticians, academicians, developers, scientists, practitioners, students, and educators seeking current research on the use of artificial neural networks in diagnosing and solving nonparametric problems.
Machine Learning For Absolute Beginners
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Author : Jonathan Fitzpatrick
language : it
Publisher: Independently Published
Release Date : 2019-11-29
Machine Learning For Absolute Beginners written by Jonathan Fitzpatrick and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-29 with categories.
Different computer concepts have been misused and sometimes interchanged, leading to confusion, especially for new computer users and researchers. However, the knowledge of computer studies terms these concepts, which are almost similar but differ from each other. Besides, all these concepts of computer systems, both hardware and software are connected or depend on each other in different ways. As such, this book is what you have been waiting for to learn these terms, which seem to represent a similar computer process. The metrics of how broad computer studies do not matter, but the primary understanding of these concepts does. Machine learning, data science, pattern recognition, artificial intelligence, and deep learning are the most commonly confused and interchanged terms used out there. Inside this book, however, you will find the descriptions of both machine learning and data science and their connections and relationship. That is, you have to initially learn and have a general idea about machine learning and data science, which therefore provides a connection between the two concepts. Inside, you will find an overview of machine learning, including the definition, building blocks, and the common types used today. On the other hand, you will also find all you need to know about data science, including the definition and a general understanding through highlighted examples. Besides, the book also details the components of data science, allowing you to note the differences and similarities with machine learning. To this end, you will then find the connection between machine learning and data science, including the similarities which confuse some individuals and the differences, which separates these two computer study concepts. Also, inside, you will find the impact of neural networks on both machine learning and pattern recognition. The book initially details about neural networks, which is an essential topic in computer studies, especially in making machines learn, think, and behave like humans. You will find a general overview of neural networks and how the human brain structure and functions contributed to the creation of learning skills in computers. Also included are the components of neural networks and the connection it has to machine learning. Neural networks provide a significant contribution to machine learning, especially in handling complex datasets. Similarly, also included in the book is the contribution of neural networks in pattern recognition. Pattern recognition is another essential form of intelligence in machines where arrangements and retrieval of information based on trends are made possible by neural networks. Inside You Will Find The general understanding of machine learning, data science, neural networks, and pattern recognition The components of machine learning, data science, and neural networks Essential types of machine learning and how they help in the creation of information used in other computer concepts Similarities and differences between machine learning and data science The connection and relationship between data science and machine learning especially when it comes to the facilitation of processes datasets analysis Neural networks in machine learning and how they learn new information Neural networks in pattern recognition as well as its benefits in distinguishing different shapes, objects and images And more...
Data Science And Its Applications
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Author : Aakanksha Sharaff
language : en
Publisher: CRC Press
Release Date : 2021-08-18
Data Science And Its Applications written by Aakanksha Sharaff and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-18 with Computers categories.
The term "data" being mostly used, experimented, analyzed, and researched, "Data Science and its Applications" finds relevance in all domains of research studies including science, engineering, technology, management, mathematics, and many more in wide range of applications such as sentiment analysis, social medial analytics, signal processing, gene analysis, market analysis, healthcare, bioinformatics etc. The book on Data Science and its applications discusses about data science overview, scientific methods, data processing, extraction of meaningful information from data, and insight for developing the concept from different domains, highlighting mathematical and statistical models, operations research, computer programming, machine learning, data visualization, pattern recognition and others. The book also highlights data science implementation and evaluation of performance in several emerging applications such as information retrieval, cognitive science, healthcare, and computer vision. The data analysis covers the role of data science depicting different types of data such as text, image, biomedical signal etc. useful for a wide range of real time applications. The salient features of the book are: Overview, Challenges and Opportunities in Data Science and Real Time Applications Addressing Big Data Issues Useful Machine Learning Methods Disease Detection and Healthcare Applications utilizing Data Science Concepts and Deep Learning Applications in Stock Market, Education, Behavior Analysis, Image Captioning, Gene Analysis and Scene Text Analysis Data Optimization Due to multidisciplinary applications of data science concepts, the book is intended for wide range of readers that include Data Scientists, Big Data Analysists, Research Scholars engaged in Data Science and Machine Learning applications.
Deep Learning Practical Neural Networks With Java
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Author : Yusuke Sugomori
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-06-08
Deep Learning Practical Neural Networks With Java written by Yusuke Sugomori and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-08 with Computers categories.
Build and run intelligent applications by leveraging key Java machine learning libraries About This Book Develop a sound strategy to solve predictive modelling problems using the most popular machine learning Java libraries. Explore a broad variety of data processing, machine learning, and natural language processing through diagrams, source code, and real-world applications This step-by-step guide will help you solve real-world problems and links neural network theory to their application Who This Book Is For This course is intended for data scientists and Java developers who want to dive into the exciting world of deep learning. It will get you up and running quickly and provide you with the skills you need to successfully create, customize, and deploy machine learning applications in real life. What You Will Learn Get a practical deep dive into machine learning and deep learning algorithms Explore neural networks using some of the most popular Deep Learning frameworks Dive into Deep Belief Nets and Stacked Denoising Autoencoders algorithms Apply machine learning to fraud, anomaly, and outlier detection Experiment with deep learning concepts, algorithms, and the toolbox for deep learning Select and split data sets into training, test, and validation, and explore validation strategies Apply the code generated in practical examples, including weather forecasting and pattern recognition In Detail Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognitionStarting with an introduction to basic machine learning algorithms, this course takes you further into this vital world of stunning predictive insights and remarkable machine intelligence. This course helps you solve challenging problems in image processing, speech recognition, language modeling. You will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text. You will also work with examples such as weather forecasting, disease diagnosis, customer profiling, generalization, extreme machine learning and more. By the end of this course, you will have all the knowledge you need to perform deep learning on your system with varying complexity levels, to apply them to your daily work. The course provides you with highly practical content explaining deep learning with Java, from the following Packt books: Java Deep Learning Essentials Machine Learning in Java Neural Network Programming with Java, Second Edition Style and approach This course aims to create a smooth learning path that will teach you how to effectively use deep learning with Java with other de facto components to get the most out of it. Through this comprehensive course, you'll learn the basics of predictive modelling and progress to solve real-world problems and links neural network theory to their application
Data Science
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Author : Gyanendra K. Verma
language : en
Publisher: Springer Nature
Release Date : 2021-08-19
Data Science written by Gyanendra K. Verma and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-19 with Computers categories.
This book targets an audience with a basic understanding of deep learning, its architectures, and its application in the multimedia domain. Background in machine learning is helpful in exploring various aspects of deep learning. Deep learning models have a major impact on multimedia research and raised the performance bar substantially in many of the standard evaluations. Moreover, new multi-modal challenges are tackled, which older systems would not have been able to handle. However, it is very difficult to comprehend, let alone guide, the process of learning in deep neural networks, there is an air of uncertainty about exactly what and how these networks learn. By the end of the book, the readers will have an understanding of different deep learning approaches, models, pre-trained models, and familiarity with the implementation of various deep learning algorithms using various frameworks and libraries.
Data Mining And Machine Learning Applications
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Author : Rohit Raja
language : en
Publisher: John Wiley & Sons
Release Date : 2022-01-26
Data Mining And Machine Learning Applications written by Rohit Raja and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-26 with Computers categories.
DATA MINING AND MACHINE LEARNING APPLICATIONS The book elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data. Massive datasets can be classified and clustered to obtain accurate results. The most common technologies used include classification and clustering methods. Accuracy and error rates are calculated for regression and classification and clustering to find actual results through algorithms like support vector machines and neural networks with forward and backward propagation. Applications include fraud detection, image processing, medical diagnosis, weather prediction, e-commerce and so forth. The book features: A review of the state-of-the-art in data mining and machine learning, A review and description of the learning methods in human-computer interaction, Implementation strategies and future research directions used to meet the design and application requirements of several modern and real-time applications for a long time, The scope and implementation of a majority of data mining and machine learning strategies. A discussion of real-time problems. Audience Industry and academic researchers, scientists, and engineers in information technology, data science and machine and deep learning, as well as artificial intelligence more broadly.
Machine Learning And Its Applications
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Author : Georgios Paliouras
language : en
Publisher: Springer Science & Business Media
Release Date : 2001-08-01
Machine Learning And Its Applications written by Georgios Paliouras and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-08-01 with Computers categories.
In recent years machine learning has made its way from artificial intelligence into areas of administration, commerce, and industry. Data mining is perhaps the most widely known demonstration of this migration, complemented by less publicized applications of machine learning like adaptive systems in industry, financial prediction, medical diagnosis and the construction of user profiles for Web browsers. This book presents the capabilities of machine learning methods and ideas on how these methods could be used to solve real-world problems. The first ten chapters assess the current state of the art of machine learning, from symbolic concept learning and conceptual clustering to case-based reasoning, neural networks, and genetic algorithms. The second part introduces the reader to innovative applications of ML techniques in fields such as data mining, knowledge discovery, human language technology, user modeling, data analysis, discovery science, agent technology, finance, etc.
Machine Learning For Beginners
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Author : Samuel Hack
language : en
Publisher:
Release Date : 2021-01-16
Machine Learning For Beginners written by Samuel Hack and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-16 with Computers categories.
Are you interested in learning about the amazing capabilities of machine learning, but you're worried it will be just too complicated? Or are you a programmer looking for a solid introduction into this field? Then keep reading Machine learning is an incredible technology which we're only just beginning to understand. Those who break into this industry early will reap the rewards as this field grows more and more important to businesses the world over. And the good news is, it's not too late to start! This guide breaks down the fundamentals of machine learning in a way that anyone can understand. With reference to the different kinds of machine learning models, neural networks, and the way these models learn data, you'll find everything you need to know to get started with machine learning in a concise, easy-to-understand way. Here's what you'll discover inside: What is Artificial Intelligence Really, and Why is it So Powerful? Choosing the Right Kind of Machine Learning Model for You An Introduction to Statistics Supervised and Unsupervised Learning The Power of Neural Networks Reinforcement Learning and Ensemble Modeling "Random Forests" and Decision Trees Must-Have Programming Tools And Much More! Whether you're already a programmer or if you're a complete beginner, now you can break into machine learning in no time! Covering all the basics from simple decision trees to the complex decision-making processes which mirror our own brains, Machine Learning for Beginners is your comprehensive introduction to this amazing field! Buy Now to Discover How You Can Get Started With Machine Learning Today!