Machine Learning Theory And Applications

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Machine Learning

Seyedeh Leili Mirtaheri,Reza Shahbazian
Machine Learning Book PDF

Author : Seyedeh Leili Mirtaheri,Reza Shahbazian
Publisher : CRC Press
Page : 212 pages
File Size : 53,9 Mb
Release : 2022-09-29
Category : Business & Economics
ISBN : 9781000737691

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Machine Learning by Seyedeh Leili Mirtaheri,Reza Shahbazian Pdf

The book reviews core concepts of machine learning (ML) while focusing on modern applications. It is aimed at those who want to advance their understanding of ML by providing technical and practical insights. It does not use complicated mathematics to explain how to benefit from ML algorithms. Unlike the existing literature, this work provides the core concepts with emphasis on fresh ideas and real application scenarios. It starts with the basic concepts of ML and extends the concepts to the different deep learning algorithms. The book provides an introduction and main elements of evaluation tools with Python and walks you through the recent applications of ML in self-driving cars, cognitive decision making, communication networks, security, and signal processing. The concept of generative networks is also presented and focuses on GANs as a tool to improve the performance of existing algorithms. In summary, this book provides a comprehensive technological path from fundamental theories to the categorization of existing algorithms, covers state-of-the-art, practical evaluation tools and methods to empower you to use synthetic data to improve the performance of applications.

Machine Learning Theory and Applications

Xavier Vasques
Machine Learning Theory and Applications Book PDF

Author : Xavier Vasques
Publisher : John Wiley & Sons
Page : 516 pages
File Size : 55,5 Mb
Release : 2024-03-06
Category : Computers
ISBN : 9781394220618

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Machine Learning Theory and Applications by Xavier Vasques Pdf

Enables readers to understand mathematical concepts behind data engineering and machine learning algorithms and apply them using open-source Python libraries Machine Learning Theory and Applications delves into the realm of machine learning and deep learning, exploring their practical applications by comprehending mathematical concepts and implementing them in real-world scenarios using Python and renowned open-source libraries. This comprehensive guide covers a wide range of topics, including data preparation, feature engineering techniques, commonly utilized machine learning algorithms like support vector machines and neural networks, as well as generative AI and foundation models. To facilitate the creation of machine learning pipelines, a dedicated open-source framework named hephAIstos has been developed exclusively for this book. Moreover, the text explores the fascinating domain of quantum machine learning and offers insights on executing machine learning applications across diverse hardware technologies such as CPUs, GPUs, and QPUs. Finally, the book explains how to deploy trained models through containerized applications using Kubernetes and OpenShift, as well as their integration through machine learning operations (MLOps). Additional topics covered in Machine Learning Theory and Applications include: Current use cases of AI, including making predictions, recognizing images and speech, performing medical diagnoses, creating intelligent supply chains, natural language processing, and much more Classical and quantum machine learning algorithms such as quantum-enhanced Support Vector Machines (QSVMs), QSVM multiclass classification, quantum neural networks, and quantum generative adversarial networks (qGANs) Different ways to manipulate data, such as handling missing data, analyzing categorical data, or processing time-related data Feature rescaling, extraction, and selection, and how to put your trained models to life and production through containerized applications Machine Learning Theory and Applications is an essential resource for data scientists, engineers, and IT specialists and architects, as well as students in computer science, mathematics, and bioinformatics. The reader is expected to understand basic Python programming and libraries such as NumPy or Pandas and basic mathematical concepts, especially linear algebra.

Handbook of Statistics

Anonim
Handbook of Statistics Book PDF

Author : Anonim
Publisher : Newnes
Page : 552 pages
File Size : 51,8 Mb
Release : 2013-05-16
Category : Mathematics
ISBN : 9780444538666

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Handbook of Statistics by Anonim Pdf

Statistical learning and analysis techniques have become extremely important today, given the tremendous growth in the size of heterogeneous data collections and the ability to process it even from physically distant locations. Recent advances made in the field of machine learning provide a strong framework for robust learning from the diverse corpora and continue to impact a variety of research problems across multiple scientific disciplines. The aim of this handbook is to familiarize beginners as well as experts with some of the recent techniques in this field. The Handbook is divided in two sections: Theory and Applications, covering machine learning, data analytics, biometrics, document recognition and security. very relevant to current research challenges faced in various fields self-contained reference to machine learning emphasis on applications-oriented techniques

Understanding Machine Learning

Shai Shalev-Shwartz,Shai Ben-David
Understanding Machine Learning Book PDF

Author : Shai Shalev-Shwartz,Shai Ben-David
Publisher : Cambridge University Press
Page : 415 pages
File Size : 49,7 Mb
Release : 2014-05-19
Category : Computers
ISBN : 9781107057135

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Understanding Machine Learning by Shai Shalev-Shwartz,Shai Ben-David Pdf

Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.

Mathematical Theories of Machine Learning - Theory and Applications

Bin Shi,S. S. Iyengar
Mathematical Theories of Machine Learning Theory and Applications Book PDF

Author : Bin Shi,S. S. Iyengar
Publisher : Springer
Page : 133 pages
File Size : 41,7 Mb
Release : 2019-06-12
Category : Technology & Engineering
ISBN : 9783030170769

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Mathematical Theories of Machine Learning - Theory and Applications by Bin Shi,S. S. Iyengar Pdf

This book studies mathematical theories of machine learning. The first part of the book explores the optimality and adaptivity of choosing step sizes of gradient descent for escaping strict saddle points in non-convex optimization problems. In the second part, the authors propose algorithms to find local minima in nonconvex optimization and to obtain global minima in some degree from the Newton Second Law without friction. In the third part, the authors study the problem of subspace clustering with noisy and missing data, which is a problem well-motivated by practical applications data subject to stochastic Gaussian noise and/or incomplete data with uniformly missing entries. In the last part, the authors introduce an novel VAR model with Elastic-Net regularization and its equivalent Bayesian model allowing for both a stable sparsity and a group selection.

Deep Learning: Fundamentals, Theory and Applications

Kaizhu Huang,Amir Hussain,Qiu-Feng Wang,Rui Zhang
Deep Learning Fundamentals Theory and Applications Book PDF

Author : Kaizhu Huang,Amir Hussain,Qiu-Feng Wang,Rui Zhang
Publisher : Springer
Page : 163 pages
File Size : 45,5 Mb
Release : 2019-02-15
Category : Medical
ISBN : 9783030060732

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Deep Learning: Fundamentals, Theory and Applications by Kaizhu Huang,Amir Hussain,Qiu-Feng Wang,Rui Zhang Pdf

The purpose of this edited volume is to provide a comprehensive overview on the fundamentals of deep learning, introduce the widely-used learning architectures and algorithms, present its latest theoretical progress, discuss the most popular deep learning platforms and data sets, and describe how many deep learning methodologies have brought great breakthroughs in various applications of text, image, video, speech and audio processing. Deep learning (DL) has been widely considered as the next generation of machine learning methodology. DL attracts much attention and also achieves great success in pattern recognition, computer vision, data mining, and knowledge discovery due to its great capability in learning high-level abstract features from vast amount of data. This new book will not only attempt to provide a general roadmap or guidance to the current deep learning methodologies, but also present the challenges and envision new perspectives which may lead to further breakthroughs in this field. This book will serve as a useful reference for senior (undergraduate or graduate) students in computer science, statistics, electrical engineering, as well as others interested in studying or exploring the potential of exploiting deep learning algorithms. It will also be of special interest to researchers in the area of AI, pattern recognition, machine learning and related areas, alongside engineers interested in applying deep learning models in existing or new practical applications.

Metaheuristics in Machine Learning: Theory and Applications

Diego Oliva
Metaheuristics in Machine Learning Theory and Applications Book PDF

Author : Diego Oliva
Publisher : Springer Nature
Page : 765 pages
File Size : 48,7 Mb
Release : 2024-04-27
Category : Computational intelligence
ISBN : 9783030705428

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Metaheuristics in Machine Learning: Theory and Applications by Diego Oliva Pdf

This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities.

Machine Learning for Audio, Image and Video Analysis

Francesco Camastra,Alessandro Vinciarelli
Machine Learning for Audio Image and Video Analysis Book PDF

Author : Francesco Camastra,Alessandro Vinciarelli
Publisher : Springer
Page : 561 pages
File Size : 49,7 Mb
Release : 2015-07-21
Category : Computers
ISBN : 9781447167358

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Machine Learning for Audio, Image and Video Analysis by Francesco Camastra,Alessandro Vinciarelli Pdf

This second edition focuses on audio, image and video data, the three main types of input that machines deal with when interacting with the real world. A set of appendices provides the reader with self-contained introductions to the mathematical background necessary to read the book. Divided into three main parts, From Perception to Computation introduces methodologies aimed at representing the data in forms suitable for computer processing, especially when it comes to audio and images. Whilst the second part, Machine Learning includes an extensive overview of statistical techniques aimed at addressing three main problems, namely classification (automatically assigning a data sample to one of the classes belonging to a predefined set), clustering (automatically grouping data samples according to the similarity of their properties) and sequence analysis (automatically mapping a sequence of observations into a sequence of human-understandable symbols). The third part Applications shows how the abstract problems defined in the second part underlie technologies capable to perform complex tasks such as the recognition of hand gestures or the transcription of handwritten data. Machine Learning for Audio, Image and Video Analysis is suitable for students to acquire a solid background in machine learning as well as for practitioners to deepen their knowledge of the state-of-the-art. All application chapters are based on publicly available data and free software packages, thus allowing readers to replicate the experiments.

Machine Learning Paradigms

Maria Virvou,Efthimios Alepis,George A. Tsihrintzis,Lakhmi C. Jain
Machine Learning Paradigms Book PDF

Author : Maria Virvou,Efthimios Alepis,George A. Tsihrintzis,Lakhmi C. Jain
Publisher : Springer
Page : 223 pages
File Size : 40,6 Mb
Release : 2019-03-16
Category : Technology & Engineering
ISBN : 9783030137434

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Machine Learning Paradigms by Maria Virvou,Efthimios Alepis,George A. Tsihrintzis,Lakhmi C. Jain Pdf

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.

Manifold Learning Theory and Applications

Yunqian Ma,Yun Fu
Manifold Learning Theory and Applications Book PDF

Author : Yunqian Ma,Yun Fu
Publisher : CRC Press
Page : 410 pages
File Size : 47,8 Mb
Release : 2011-12-20
Category : Business & Economics
ISBN : 9781466558878

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Manifold Learning Theory and Applications by Yunqian Ma,Yun Fu Pdf

Trained to extract actionable information from large volumes of high-dimensional data, engineers and scientists often have trouble isolating meaningful low-dimensional structures hidden in their high-dimensional observations. Manifold learning, a groundbreaking technique designed to tackle these issues of dimensionality reduction, finds widespread

Machine Learning for Spatial Environmental Data

Mikhail Kanevski,Alexi Pozdnukhov,Vadim Timonin
Machine Learning for Spatial Environmental Data Book PDF

Author : Mikhail Kanevski,Alexi Pozdnukhov,Vadim Timonin
Publisher : EPFL Press
Page : 444 pages
File Size : 43,6 Mb
Release : 2009-06-09
Category : Science
ISBN : 0849382378

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Machine Learning for Spatial Environmental Data by Mikhail Kanevski,Alexi Pozdnukhov,Vadim Timonin Pdf

Acompanyament de CD-RM conté MLO software, la guia d'MLO (pdf) i exemples de dades.

Theory and Novel Applications of Machine Learning

Er Meng Joo,Yi Zhou
Theory and Novel Applications of Machine Learning Book PDF

Author : Er Meng Joo,Yi Zhou
Publisher : BoD – Books on Demand
Page : 390 pages
File Size : 49,7 Mb
Release : 2009-01-01
Category : Computers
ISBN : 9783902613554

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Theory and Novel Applications of Machine Learning by Er Meng Joo,Yi Zhou Pdf

Even since computers were invented, many researchers have been trying to understand how human beings learn and many interesting paradigms and approaches towards emulating human learning abilities have been proposed. The ability of learning is one of the central features of human intelligence, which makes it an important ingredient in both traditional Artificial Intelligence (AI) and emerging Cognitive Science. Machine Learning (ML) draws upon ideas from a diverse set of disciplines, including AI, Probability and Statistics, Computational Complexity, Information Theory, Psychology and Neurobiology, Control Theory and Philosophy. ML involves broad topics including Fuzzy Logic, Neural Networks (NNs), Evolutionary Algorithms (EAs), Probability and Statistics, Decision Trees, etc. Real-world applications of ML are widespread such as Pattern Recognition, Data Mining, Gaming, Bio-science, Telecommunications, Control and Robotics applications. This books reports the latest developments and futuristic trends in ML.

Machine Learning and Its Applications

Georgios Paliouras,Vangelis Karkaletsis,Constantine D. Spyropoulos
Machine Learning and Its Applications Book PDF

Author : Georgios Paliouras,Vangelis Karkaletsis,Constantine D. Spyropoulos
Publisher : Springer
Page : 324 pages
File Size : 47,5 Mb
Release : 2003-06-29
Category : Computers
ISBN : 9783540446736

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Machine Learning and Its Applications by Georgios Paliouras,Vangelis Karkaletsis,Constantine D. Spyropoulos Pdf

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 Algorithms and Applications

Mettu Srinivas,G. Sucharitha,Anjanna Matta
Machine Learning Algorithms and Applications Book PDF

Author : Mettu Srinivas,G. Sucharitha,Anjanna Matta
Publisher : John Wiley & Sons
Page : 372 pages
File Size : 54,7 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.

Machine Learning Paradigms: Theory and Application

Aboul Ella Hassanien
Machine Learning Paradigms Theory and Application Book PDF

Author : Aboul Ella Hassanien
Publisher : Springer
Page : 474 pages
File Size : 41,8 Mb
Release : 2018-12-08
Category : Technology & Engineering
ISBN : 9783030023577

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Machine Learning Paradigms: Theory and Application by Aboul Ella Hassanien Pdf

The book focuses on machine learning. Divided into three parts, the first part discusses the feature selection problem. The second part then describes the application of machine learning in the classification problem, while the third part presents an overview of real-world applications of swarm-based optimization algorithms. The concept of machine learning (ML) is not new in the field of computing. However, due to the ever-changing nature of requirements in today’s world it has emerged in the form of completely new avatars. Now everyone is talking about ML-based solution strategies for a given problem set. The book includes research articles and expository papers on the theory and algorithms of machine learning and bio-inspiring optimization, as well as papers on numerical experiments and real-world applications.