Implementations And Applications Of Machine Learning

Author : Saad Subair,Christopher Thron
Publisher : Springer Nature
Page : 288 pages
File Size : 52,5 Mb
Release : 2020-04-23
Category : Technology & Engineering
ISBN : 9783030378301

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Implementations and Applications of Machine Learning by Saad Subair,Christopher Thron Pdf

This book provides step-by-step explanations of successful implementations and practical applications of machine learning. The book’s GitHub page contains software codes to assist readers in adapting materials and methods for their own use. A wide variety of applications are discussed, including wireless mesh network and power systems optimization; computer vision; image and facial recognition; protein prediction; data mining; and data discovery. Numerous state-of-the-art machine learning techniques are employed (with detailed explanations), including biologically-inspired optimization (genetic and other evolutionary algorithms, swarm intelligence); Viola Jones face detection; Gaussian mixture modeling; support vector machines; deep convolutional neural networks with performance enhancement techniques (including network design, learning rate optimization, data augmentation, transfer learning); spiking neural networks and timing dependent plasticity; frequent itemset mining; binary classification; and dynamic programming. This book provides valuable information on effective, cutting-edge techniques, and approaches for students, researchers, practitioners, and teachers in the field of machine learning.

Author : Sathiyamoorthi Velayutham
Publisher : IGI Global, Engineering Science Reference
Page : 0 pages
File Size : 52,6 Mb
Release : 2019-08-23
Category : Computers
ISBN : 1522599053

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Handbook of Research on Applications and Implementations of Machine Learning Techniques by Sathiyamoorthi Velayutham Pdf

"This book examines the practical applications and implementation of various machine learning techniques in various fields such as agriculture, medical, image processing, and networking"--

Author : Kashyap, Ramgopal,Kumar, A.V. Senthil
Publisher : IGI Global
Page : 293 pages
File Size : 49,5 Mb
Release : 2019-10-04
Category : Computers
ISBN : 9781799801849

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Challenges and Applications for Implementing Machine Learning in Computer Vision by Kashyap, Ramgopal,Kumar, A.V. Senthil Pdf

Machine learning allows for non-conventional and productive answers for issues within various fields, including problems related to visually perceptive computers. Applying these strategies and algorithms to the area of computer vision allows for higher achievement in tasks such as spatial recognition, big data collection, and image processing. There is a need for research that seeks to understand the development and efficiency of current methods that enable machines to see. Challenges and Applications for Implementing Machine Learning in Computer Vision is a collection of innovative research that combines theory and practice on adopting the latest deep learning advancements for machines capable of visual processing. Highlighting a wide range of topics such as video segmentation, object recognition, and 3D modelling, this publication is ideally designed for computer scientists, medical professionals, computer engineers, information technology practitioners, industry experts, scholars, researchers, and students seeking current research on the utilization of evolving computer vision techniques.

Author : Aleksandar Kartelj,Veljko Milutinović,Nenad Mitić
Publisher : Engineering Science Reference
Page : 300 pages
File Size : 53,9 Mb
Release : 2022
Category : Algorithms
ISBN : 1799883507

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Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms by Aleksandar Kartelj,Veljko Milutinović,Nenad Mitić Pdf

"This is a reference book for experienced professionals, that treats four widely used data-mining algorithms in a novel way, offering a basic introduction with issues of importance, advantages and disadvantages of these algorithms"--

Author : Sandeep Saini,Kusum Lata,G.R. Sinha
Publisher : CRC Press
Page : 329 pages
File Size : 50,5 Mb
Release : 2021-12-30
Category : Technology & Engineering
ISBN : 9781000523812

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VLSI and Hardware Implementations using Modern Machine Learning Methods by Sandeep Saini,Kusum Lata,G.R. Sinha Pdf

Provides the details of state-of-the-art machine learning methods used in VLSI Design. Discusses hardware implementation and device modeling pertaining to machine learning algorithms. Explores machine learning for various VLSI architectures and reconfigurable computing. Illustrate latest techniques for device size and feature optimization. Highlight latest case studies and reviews of the methods used for hardware implementation.

Author : Solanki, Arun,Kumar, Sandeep,Nayyar, Anand
Publisher : IGI Global
Page : 674 pages
File Size : 40,8 Mb
Release : 2019-12-13
Category : Computers
ISBN : 9781522596455

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Handbook of Research on Emerging Trends and Applications of Machine Learning by Solanki, Arun,Kumar, Sandeep,Nayyar, Anand Pdf

As today’s world continues to advance, Artificial Intelligence (AI) is a field that has become a staple of technological development and led to the advancement of numerous professional industries. An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world. The Handbook of Research on Emerging Trends and Applications of Machine Learning provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, this book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science. While highlighting topics including image processing, predictive analytics, and smart grid management, this book is ideally designed for developers, data scientists, business analysts, information architects, finance agents, healthcare professionals, researchers, retail traders, professors, and graduate students seeking current research on the benefits, implementations, and trends of machine learning.

Author : Mahrishi, Mehul,Hiran, Kamal Kant,Meena, Gaurav,Sharma, Paawan
Publisher : IGI Global
Page : 344 pages
File Size : 41,6 Mb
Release : 2020-04-24
Category : Computers
ISBN : 9781799830979

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Machine Learning and Deep Learning in Real-Time Applications by Mahrishi, Mehul,Hiran, Kamal Kant,Meena, Gaurav,Sharma, Paawan Pdf

Artificial intelligence and its various components are rapidly engulfing almost every professional industry. Specific features of AI that have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher levels of performance and efficiency, creating a wide span of industrial applications. However, there is a lack of research on the specific uses of machine/deep learning in the professional realm. Machine Learning and Deep Learning in Real-Time Applications provides emerging research exploring the theoretical and practical aspects of machine learning and deep learning and their implementations as well as their ability to solve real-world problems within several professional disciplines including healthcare, business, and computer science. Featuring coverage on a broad range of topics such as image processing, medical improvements, and smart grids, this book is ideally designed for researchers, academicians, scientists, industry experts, scholars, IT professionals, engineers, and students seeking current research on the multifaceted uses and implementations of machine learning and deep learning across the globe.

Author : Dinesh Goyal,Amit Kumar Gupta,Vincenzo Piuri,Maria Ganzha,Marcin Paprzycki
Publisher : Springer Nature
Page : 751 pages
File Size : 48,9 Mb
Release : 2021-01-22
Category : Technology & Engineering
ISBN : 9789811596896

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Proceedings of the Second International Conference on Information Management and Machine Intelligence by Dinesh Goyal,Amit Kumar Gupta,Vincenzo Piuri,Maria Ganzha,Marcin Paprzycki Pdf

This book features selected papers presented at Second International Conference on International Conference on Information Management & Machine Intelligence (ICIMMI 2020) held at Poornima Institute of Engineering & Technology, Jaipur, Rajasthan, India during 24 – 25 July 2020. It covers a range of topics, including data analytics; AI; machine and deep learning; information management, security, processing techniques and interpretation; applications of artificial intelligence in soft computing and pattern recognition; cloud-based applications for machine learning; application of IoT in power distribution systems; as well as wireless sensor networks and adaptive wireless communication.

Author : Sathiyamoorthi Velayutham
Publisher : Unknown
Page : 0 pages
File Size : 43,5 Mb
Release : 2020
Category : Machine learning
ISBN : 152312914X

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Handbook of Research on Applications and Implementations of Machine Learning Techniques by Sathiyamoorthi Velayutham Pdf

Author : Suman Lata Tripathi,Mufti Mahmud
Publisher : John Wiley & Sons
Page : 277 pages
File Size : 45,6 Mb
Release : 2023-10-03
Category : Computers
ISBN : 9781394185849

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Explainable Machine Learning Models and Architectures by Suman Lata Tripathi,Mufti Mahmud Pdf

EXPLAINABLE MACHINE LEARNING MODELS AND ARCHITECTURES This cutting-edge new volume covers the hardware architecture implementation, the software implementation approach, and the efficient hardware of machine learning applications. Machine learning and deep learning modules are now an integral part of many smart and automated systems where signal processing is performed at different levels. Signal processing in the form of text, images, or video needs large data computational operations at the desired data rate and accuracy. Large data requires more use of integrated circuit (IC) area with embedded bulk memories that further lead to more IC area. Trade-offs between power consumption, delay and IC area are always a concern of designers and researchers. New hardware architectures and accelerators are needed to explore and experiment with efficient machine-learning models. Many real-time applications like the processing of biomedical data in healthcare, smart transportation, satellite image analysis, and IoT-enabled systems have a lot of scope for improvements in terms of accuracy, speed, computational powers, and overall power consumption. This book deals with the efficient machine and deep learning models that support high-speed processors with reconfigurable architectures like graphic processing units (GPUs) and field programmable gate arrays (FPGAs), or any hybrid system. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.

Author : Rohit Raja,Kapil Kumar Nagwanshi,Sandeep Kumar,K. Ramya Laxmi
Publisher : John Wiley & Sons
Page : 500 pages
File Size : 41,6 Mb
Release : 2022-01-26
Category : Computers
ISBN : 9781119792505

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Data Mining and Machine Learning Applications by Rohit Raja,Kapil Kumar Nagwanshi,Sandeep Kumar,K. Ramya Laxmi Pdf

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.

Author : Milutinovi?, Veljko,Miti?, Nenad,Kartelj, Aleksandar,Kotlar, Miloš
Publisher : IGI Global
Page : 296 pages
File Size : 40,7 Mb
Release : 2022-03-11
Category : Computers
ISBN : 9781799883524

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Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms by Milutinovi?, Veljko,Miti?, Nenad,Kartelj, Aleksandar,Kotlar, Miloš Pdf

Based on current literature and cutting-edge advances in the machine learning field, there are four algorithms whose usage in new application domains must be explored: neural networks, rule induction algorithms, tree-based algorithms, and density-based algorithms. A number of machine learning related algorithms have been derived from these four algorithms. Consequently, they represent excellent underlying methods for extracting hidden knowledge from unstructured data, as essential data mining tasks. Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms presents widely used data-mining algorithms and explains their advantages and disadvantages, their mathematical treatment, applications, energy efficient implementations, and more. It presents research of energy efficient accelerators for machine learning algorithms. Covering topics such as control-flow implementation, approximate computing, and decision tree algorithms, this book is an essential resource for computer scientists, engineers, students and educators of higher education, researchers, and academicians.

Author : Subhendu Kumar Pani,Somanath Tripathy,George Jandieri,Sumit Kundu,Talal Ashraf Butt
Publisher : CRC Press
Page : 346 pages
File Size : 47,7 Mb
Release : 2022-09-01
Category : Technology & Engineering
ISBN : 9781000793550

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Applications of Machine Learning in Big-Data Analytics and Cloud Computing by Subhendu Kumar Pani,Somanath Tripathy,George Jandieri,Sumit Kundu,Talal Ashraf Butt Pdf

Cloud Computing and Big Data technologies have become the new descriptors of the digital age. The global amount of digital data has increased more than nine times in volume in just five years and by 2030 its volume may reach a staggering 65 trillion gigabytes. This explosion of data has led to opportunities and transformation in various areas such as healthcare, enterprises, industrial manufacturing and transportation. New Cloud Computing and Big Data tools endow researchers and analysts with novel techniques and opportunities to collect, manage and analyze the vast quantities of data. In Cloud and Big Data Analytics, the two areas of Swarm Intelligence and Deep Learning are a developing type of Machine Learning techniques that show enormous potential for solving complex business problems. Deep Learning enables computers to analyze large quantities of unstructured and binary data and to deduce relationships without requiring specific models or programming instructions. This book introduces the state-of-the-art trends and advances in the use of Machine Learning in Cloud and Big Data Analytics. The book will serve as a reference for Data Scientists, systems architects, developers, new researchers and graduate level students in Computer and Data science. The book will describe the concepts necessary to understand current Machine Learning issues, challenges and possible solutions as well as upcoming trends in Big Data Analytics.

Author : Giuseppe Bonaccorso
Publisher : Packt Publishing Ltd
Page : 799 pages
File Size : 53,8 Mb
Release : 2020-01-31
Category : Computers
ISBN : 9781838821913

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Mastering Machine Learning Algorithms by Giuseppe Bonaccorso Pdf

Updated and revised second edition of the bestselling guide to exploring and mastering the most important algorithms for solving complex machine learning problems Key FeaturesUpdated to include new algorithms and techniquesCode updated to Python 3.8 & TensorFlow 2.x New coverage of regression analysis, time series analysis, deep learning models, and cutting-edge applicationsBook Description Mastering Machine Learning Algorithms, Second Edition helps you harness the real power of machine learning algorithms in order to implement smarter ways of meeting today's overwhelming data needs. This newly updated and revised guide will help you master algorithms used widely in semi-supervised learning, reinforcement learning, supervised learning, and unsupervised learning domains. You will use all the modern libraries from the Python ecosystem – including NumPy and Keras – to extract features from varied complexities of data. Ranging from Bayesian models to the Markov chain Monte Carlo algorithm to Hidden Markov models, this machine learning book teaches you how to extract features from your dataset, perform complex dimensionality reduction, and train supervised and semi-supervised models by making use of Python-based libraries such as scikit-learn. You will also discover practical applications for complex techniques such as maximum likelihood estimation, Hebbian learning, and ensemble learning, and how to use TensorFlow 2.x to train effective deep neural networks. By the end of this book, you will be ready to implement and solve end-to-end machine learning problems and use case scenarios. What you will learnUnderstand the characteristics of a machine learning algorithmImplement algorithms from supervised, semi-supervised, unsupervised, and RL domainsLearn how regression works in time-series analysis and risk predictionCreate, model, and train complex probabilistic models Cluster high-dimensional data and evaluate model accuracy Discover how artificial neural networks work – train, optimize, and validate them Work with autoencoders, Hebbian networks, and GANsWho this book is for This book is for data science professionals who want to delve into complex ML algorithms to understand how various machine learning models can be built. Knowledge of Python programming is required.

Author : Valentina Emilia Balas,Sanjiban Sekhar Roy,Dharmendra Sharma,Pijush Samui
Publisher : Springer
Page : 383 pages
File Size : 40,9 Mb
Release : 2019-02-25
Category : Technology & Engineering
ISBN : 9783030114794

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Handbook of Deep Learning Applications by Valentina Emilia Balas,Sanjiban Sekhar Roy,Dharmendra Sharma,Pijush Samui Pdf

This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.