Machine Learning And It S Techniques
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Machine Learning And It S Techniques
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Author : Dr. Lakshmi Anusha Kothamasu
language : en
Publisher: Academic Guru Publishing House
Release Date : 2024-07-29
Machine Learning And It S Techniques written by Dr. Lakshmi Anusha Kothamasu and has been published by Academic Guru Publishing House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-29 with Study Aids categories.
The book "Machine Learning and Its Techniques" provides a thorough examination of the fundamental approaches and uses of machine learning. The book is designed to take readers from fundamental ideas to more complex subjects, guaranteeing a deep comprehension of the material. Neural networks, deep learning, reinforcement learning, and both supervised and unsupervised learning are important subjects. The theoretical ideas in each chapter are followed by real-world examples and learning-enhancement activities. Common machine learning problems including overfitting, underfitting, and model assessment are also covered in the book. A comprehensive perspective of the discipline is provided by giving particular attention to the ethical issues and potential directions of machine learning. Readers will have acquired the information and abilities needed to use machine learning methods in an ethical and successful manner by the time they finish this book. This thorough tutorial is perfect for anybody who wants to learn more about machine learning and use it in practical situations.
Machine Learning A Comprehensive Overview Of Algorithms And Techniques
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Author :
language : en
Publisher: Xoffencerpublication
Release Date : 2023-07-04
Machine Learning A Comprehensive Overview Of Algorithms And Techniques written by and has been published by Xoffencerpublication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-04 with Computers categories.
The field of artificial intelligence (AI) and computer science known as machine learning is focused on the use of data and algorithms to simulate the method in which people learn, with the goal of continuously improving the accuracy of the simulation. Machine learning has a long and illustrious history at IBM. As a result of Arthur Samuel's study (PDF, 481 KB) (link lives outside of IBM) revolving around the game of checkers, the phrase "machine learning" is often regarded as having been first used by a member of IBM's staff. Robert Nealey, who fancied himself the world's best player at checkers, challenged an IBM 7094 computer to a match in 1962 and was defeated by the machine. This accomplishment may appear little when weighed against what is now possible, yet it is recognized as a significant turning point in the development of artificial intelligence. In the past few of decades, technical advancements in storage and processing capacity have made it possible for a number of novel products based on machine learning to become available. Some examples of these products are the recommendation engine used by Netflix and autonomous vehicles. The rapidly developing discipline of data science has an essential subfield known as machine learning. Data mining initiatives involve the training of algorithms to create classifications or predictions, as well as the discovery of critical insights, through the utilization of statistical methodologies. The subsequent decisions made inside applications and enterprises are influenced by these insights, which should ideally have an effect on key growth indicators. It is expected that there will be a greater need for data scientists in the industry as big data continues to develop and flourish. They will be expected to assist in determining the business questions that are the most pertinent, as well as the data necessary to answer those questions. Frameworks that speed up the construction of solutions are usually used while developing machine learning algorithms. Some examples of such frameworks are TensorFlow and PyTorch
Handbook Of Research On Machine Learning Techniques For Pattern Recognition And Information Security
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Author : Dua, Mohit
language : en
Publisher: IGI Global
Release Date : 2021-05-14
Handbook Of Research On Machine Learning Techniques For Pattern Recognition And Information Security written by Dua, Mohit and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-14 with Computers categories.
The artificial intelligence subset machine learning has become a popular technique in professional fields as many are finding new ways to apply this trending technology into their everyday practices. Two fields that have majorly benefited from this are pattern recognition and information security. The ability of these intelligent algorithms to learn complex patterns from data and attain new performance techniques has created a wide variety of uses and applications within the data security industry. There is a need for research on the specific uses machine learning methods have within these fields, along with future perspectives. The Handbook of Research on Machine Learning Techniques for Pattern Recognition and Information Security is a collection of innovative research on the current impact of machine learning methods within data security as well as its various applications and newfound challenges. While highlighting topics including anomaly detection systems, biometrics, and intrusion management, this book is ideally designed for industrial experts, researchers, IT professionals, network developers, policymakers, computer scientists, educators, and students seeking current research on implementing machine learning tactics to enhance the performance of information security.
Machine Learning Techniques And Principles
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Author : Dr. Harshalata J. Petkar
language : en
Publisher: Academic Guru Publishing House
Release Date : 2023-09-04
Machine Learning Techniques And Principles written by Dr. Harshalata J. Petkar and has been published by Academic Guru Publishing House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-04 with Study Aids categories.
Machine learning is a branch of AI that seeks to automate repetitive, rule-based tasks by training computers to learn from data sets with little human input. It is a technique for analyzing data that allows for the automated construction of analytical models by drawing on information in numbers, words, hyperlinks, and pictures. Applications that use machine learning take in data, analyze it, and then use automated optimization techniques to increase the precision of their results. In addition to aiding in product creation, machine learning helps businesses keep tabs on shifting client preferences and organizational tendencies. Facebook, Google, and Uber are just a few industry leaders who use machine learning extensively. Machine learning has emerged as a key differentiator for many businesses. When it comes to gathering, analyzing, and reacting to massive volumes of data, Machine Learning is employed extensively across all sectors. In one way or another, Machine Learning affects our everyday lives. The most valuable aspect of machine learning is its ability to make high-quality predictions that may direct wiser choices and prompt more effective actions in real-time with no human involvement.
Research Anthology On Machine Learning Techniques Methods And Applications
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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2022-05-13
Research Anthology On Machine Learning Techniques Methods And Applications written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-13 with Computers categories.
Machine learning continues to have myriad applications across industries and fields. To ensure this technology is utilized appropriately and to its full potential, organizations must better understand exactly how and where it can be adapted. Further study on the applications of machine learning is required to discover its best practices, challenges, and strategies. The Research Anthology on Machine Learning Techniques, Methods, and Applications provides a thorough consideration of the innovative and emerging research within the area of machine learning. The book discusses how the technology has been used in the past as well as potential ways it can be used in the future to ensure industries continue to develop and grow. Covering a range of topics such as artificial intelligence, deep learning, cybersecurity, and robotics, this major reference work is ideal for computer scientists, managers, researchers, scholars, practitioners, academicians, instructors, and students.
Machine Learning Techniques For Vlsi Chip Design
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Author : Abhishek Kumar
language : en
Publisher: John Wiley & Sons
Release Date : 2023-07-25
Machine Learning Techniques For Vlsi Chip Design written by Abhishek Kumar 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 2023-07-25 with Computers categories.
MACHINE LEARNING TECHNIQUES FOR VLSI CHIP DESIGN This cutting-edge new volume covers the hardware architecture implementation, the software implementation approach, the efficient hardware of machine learning applications with FPGA or CMOS circuits, and many other aspects and applications of machine learning techniques for VLSI chip design. Artificial intelligence (AI) and machine learning (ML) have, or will have, an impact on almost every aspect of our lives and every device that we own. AI has benefitted every industry in terms of computational speeds, accurate decision prediction, efficient machine learning (ML), and deep learning (DL) algorithms. The VLSI industry uses the electronic design automation tool (EDA), and the integration with ML helps in reducing design time and cost of production. Finding defects, bugs, and hardware Trojans in the design with ML or DL can save losses during production. Constraints to ML-DL arise when having to deal with a large set of training datasets. This book covers the learning algorithm for floor planning, routing, mask fabrication, and implementation of the computational architecture for ML-DL. The future aspect of the ML-DL algorithm is to be available in the format of an integrated circuit (IC). A user can upgrade to the new algorithm by replacing an IC. This new book mainly deals with the adaption of computation blocks like hardware accelerators and novel nano-material for them based upon their application and to create a smart solution. This exciting new volume is an invaluable reference for beginners as well as engineers, scientists, researchers, and other professionals working in the area of VLSI architecture development.
Machine Intelligence Techniques For Data Analysis And Signal Processing
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Author : Dilip Singh Sisodia
language : en
Publisher: Springer Nature
Release Date : 2023-05-30
Machine Intelligence Techniques For Data Analysis And Signal Processing written by Dilip Singh Sisodia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-30 with Technology & Engineering categories.
This book comprises the proceedings of the 4th International Conference on Machine Intelligence and Signal Processing (MISP2022). The contents of this book focus on research advancements in machine intelligence, signal processing, and applications. The book covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. It also includes the progress in signal processing to process the normal and abnormal categories of real-world signals such as signals generated from IoT devices, smart systems, speech, and videos and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG), electromyogram (EMG), etc. This book proves a valuable resource for those in academia and industry.
Recent Advances In Machine Learning Techniques And Sensor Applications For Human Emotion Activity Recognition And Support
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Author : Kyandoghere Kyamakya
language : en
Publisher: Springer Nature
Release Date : 2024-11-07
Recent Advances In Machine Learning Techniques And Sensor Applications For Human Emotion Activity Recognition And Support written by Kyandoghere Kyamakya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-07 with Computers categories.
This book explores integrating machine learning techniques and sensor applications for human emotion and activity recognition, creating personalized and effective support systems. It covers state-of-the-art machine learning techniques and large language models using multimodal sensors. Enhancing the quality of life for individuals with special needs, particularly the elderly, is a key focus in Active and Assisted Living (AAL) research. Unlike other literature, it emphasizes support mechanisms along with recognition, using metamodel integration for adaptable AAL systems. This book offers insights into technologies transforming AAL for researchers, students, and practitioners. It is a valuable resource for developing responsive and personalized support systems that enhance life quality in smart environments. It is also essential for advancing the understanding of machine learning and sensor technologies in AAL and emotion recognition.
Applying Machine Learning Techniques To Bioinformatics Few Shot And Zero Shot Methods
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Author : Lilhore, Umesh Kumar
language : en
Publisher: IGI Global
Release Date : 2024-03-22
Applying Machine Learning Techniques To Bioinformatics Few Shot And Zero Shot Methods written by Lilhore, Umesh Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-22 with Computers categories.
Why are cutting-edge data science techniques such as bioinformatics, few-shot learning, and zero-shot learning underutilized in the world of biological sciences?. In a rapidly advancing field, the failure to harness the full potential of these disciplines limits scientists’ ability to unlock critical insights into biological systems, personalized medicine, and biomarker identification. This untapped potential hinders progress and limits our capacity to tackle complex biological challenges. The solution to this issue lies within the pages of Applying Machine Learning Techniques to Bioinformatics. This book serves as a powerful resource, offering a comprehensive analysis of how these emerging disciplines can be effectively applied to the realm of biological research. By addressing these challenges and providing in-depth case studies and practical implementations, the book equips researchers, scientists, and curious minds with the knowledge and techniques needed to navigate the ever-changing landscape of bioinformatics and machine learning within the biological sciences.
Machine Learning And Deep Learning Techniques For Medical Science
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Author : K. Gayathri Devi
language : en
Publisher: CRC Press
Release Date : 2022-05-11
Machine Learning And Deep Learning Techniques For Medical Science written by K. Gayathri Devi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-11 with Technology & Engineering categories.
The application of machine learning is growing exponentially into every branch of business and science, including medical science. This book presents the integration of machine learning (ML) and deep learning (DL) algorithms that can be applied in the healthcare sector to reduce the time required by doctors, radiologists, and other medical professionals for analyzing, predicting, and diagnosing the conditions with accurate results. The book offers important key aspects in the development and implementation of ML and DL approaches toward developing prediction tools and models and improving medical diagnosis. The contributors explore the recent trends, innovations, challenges, and solutions, as well as case studies of the applications of ML and DL in intelligent system-based disease diagnosis. The chapters also highlight the basics and the need for applying mathematical aspects with reference to the development of new medical models. Authors also explore ML and DL in relation to artificial intelligence (AI) prediction tools, the discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, and pattern recognition approaches to functional magnetic resonance imaging images. This book is for students and researchers of computer science and engineering, electronics and communication engineering, and information technology; for biomedical engineering researchers, academicians, and educators; and for students and professionals in other areas of the healthcare sector. Presents key aspects in the development and the implementation of ML and DL approaches toward developing prediction tools, models, and improving medical diagnosis Discusses the recent trends, innovations, challenges, solutions, and applications of intelligent system-based disease diagnosis Examines DL theories, models, and tools to enhance health information systems Explores ML and DL in relation to AI prediction tools, discovery of drugs, neuroscience, and diagnosis in multiple imaging modalities Dr. K. Gayathri Devi is a Professor at the Department of Electronics and Communication Engineering, Dr. N.G.P Institute of Technology, Tamil Nadu, India. Dr. Kishore Balasubramanian is an Assistant Professor (Senior Scale) at the Department of EEE at Dr. Mahalingam College of Engineering & Technology, Tamil Nadu, India. Dr. Le Anh Ngoc is a Director of Swinburne Innovation Space and Professor in Swinburne University of Technology (Vietnam).