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Pattern Recognition Machine Learning Ml Using Python


Pattern Recognition Machine Learning Ml Using Python
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Pattern Recognition Machine Learning Ml Using Python


Pattern Recognition Machine Learning Ml Using Python
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Author : Dr. G. Prabaharan
language : en
Publisher: RK Publication
Release Date : 2024-05-28

Pattern Recognition Machine Learning Ml Using Python written by Dr. G. Prabaharan and has been published by RK Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-28 with Computers categories.


Pattern Recognition & Machine Learning Using Python to understanding the fundamentals of pattern recognition and machine learning, with a hands-on approach using Python. This bridges theoretical concepts with practical applications, covering algorithms, data preprocessing, and model evaluation. It includes topics such as supervised and unsupervised learning, feature selection, and deep learning techniques. Ideal for students, researchers, and professionals, the emphasizes real-world examples and Python implementations to enhance learning and skill development in data-driven problem-solving.



Thin Films Atomic Layer Deposition And 3d Printing


Thin Films Atomic Layer Deposition And 3d Printing
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Author : Kingsley Ukoba
language : en
Publisher: CRC Press
Release Date : 2023-11-29

Thin Films Atomic Layer Deposition And 3d Printing written by Kingsley Ukoba and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-29 with Technology & Engineering categories.


Thin Films, Atomic Layer Deposition, and 3D Printing explains the concept of thin films, atomic layers deposition, and the Fourth Industrial Revolution (4IR) with an aim to illustrate existing resources and give a broader perspective of the involved processes as well as provide a selection of different types of 3D printing, materials used for 3D printing, emerging trends and applications, and current top-performing 3D printers using different technologies. It covers the concept of the 4IR and its role in current and future human endeavors for both experts/nonexperts. The book includes figures, diagrams, and their applications in real-life situations. Features: Provides comprehensive material on conventional and emerging thin film, atomic layer, and additive technologies. Discusses the concept of Industry 4.0 in thin films technology. Details the preparation and properties of hybrid and scalable (ultra) thin materials for advanced applications. Explores detailed bibliometric analyses on pertinent applications. Interconnects atomic layer deposition and additive manufacturing. This book is aimed at researchers and graduate students in mechanical, materials, and metallurgical engineering.



Big Data


Big Data
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Author : Rob Botwright
language : en
Publisher: Rob Botwright
Release Date : 2024

Big Data written by Rob Botwright and has been published by Rob Botwright this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with Computers categories.


Uncover the secrets of Big Data with our comprehensive book bundle: "Big Data: Statistics, Data Mining, Analytics, and Pattern Learning." Dive into the world of data analytics and processing with Book 1, where you'll gain a solid understanding of the fundamentals necessary to navigate the vast landscape of big data. In Book 2, explore data mining techniques that allow you to extract valuable insights and patterns from large datasets. From marketing to finance and beyond, discover how to uncover hidden trends that drive informed decision-making. Ready to take your skills to the next level? Book 3 delves into advanced data science, where you'll learn to harness the power of machine learning for big data analysis. From regression analysis to neural networks, master the tools and techniques that drive predictive modeling and pattern recognition. Finally, in Book 4, learn how to design robust big data architectures that can scale to meet the needs of modern enterprises. Explore architectural patterns, scalability techniques, and fault tolerance mechanisms that ensure your systems are resilient and reliable. Whether you're a beginner looking to build a solid foundation or an experienced professional seeking to deepen your expertise, this book bundle has something for everyone. Don't miss out on this opportunity to unlock the potential of Big Data and drive innovation in your organization. Order now and embark on your journey to becoming a Big Data expert!



Introduction To Machine Learning With Security


Introduction To Machine Learning With Security
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Author : Pramod Gupta
language : en
Publisher: Springer Nature
Release Date : 2024-07-12

Introduction To Machine Learning With Security written by Pramod Gupta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-12 with Technology & Engineering categories.


This book provides an introduction to machine learning, security and cloud computing, from a conceptual level, along with their usage with underlying infrastructure. The authors emphasize fundamentals and best practices for using AI and ML in a dynamic infrastructure with cloud computing and high security, preparing readers to select and make use of appropriate techniques. Important topics are demonstrated using real applications and case studies.



Future Data And Security Engineering Big Data Security And Privacy Smart City And Industry 4 0 Applications


Future Data And Security Engineering Big Data Security And Privacy Smart City And Industry 4 0 Applications
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Author : Tran Khanh Dang
language : en
Publisher: Springer Nature
Release Date : 2020-11-19

Future Data And Security Engineering Big Data Security And Privacy Smart City And Industry 4 0 Applications written by Tran Khanh Dang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-19 with Computers categories.


This book constitutes the proceedings of the 7th International Conference on Future Data and Security Engineering, FDSE 2020, held in Quy Nhon, Vietnam, in November 2020.* The 29 full papers and 8 short were carefully reviewed and selected from 161 submissions. The selected papers are organized into the following topical headings: big data analytics and distributed systems; security and privacy engineering; industry 4.0 and smart city: data analytics and security; data analytics and healthcare systems; machine learning-based big data processing; emerging data management systems and applications; and short papers: security and data engineering. * The conference was held virtually due to the COVID-19 pandemic.



Machine Learning Animated


Machine Learning Animated
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Author : Mark Liu
language : en
Publisher: CRC Press
Release Date : 2023-10-31

Machine Learning Animated written by Mark Liu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-31 with Computers categories.


The release of ChatGPT has kicked off an arms race in Machine Learning (ML), however ML has also been described as a black box and very hard to understand. Machine Learning, Animated eases you into basic ML concepts and summarizes the learning process in three words: initialize, adjust and repeat. This is illustrated step by step with animation to show how machines learn: from initial parameter values to adjusting each step, to the final converged parameters and predictions. This book teaches readers to create their own neural networks with dense and convolutional layers, and use them to make binary and multi-category classifications. Readers will learn how to build deep learning game strategies and combine this with reinforcement learning, witnessing AI achieve super-human performance in Atari games such as Breakout, Space Invaders, Seaquest and Beam Rider. Written in a clear and concise style, illustrated with animations and images, this book is particularly appealing to readers with no background in computer science, mathematics or statistics. Access the book's repository at: https://github.com/markhliu/MLA



Pattern Recognition And Image Analysis


Pattern Recognition And Image Analysis
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Author : Aythami Morales
language : en
Publisher: Springer Nature
Release Date : 2019-09-21

Pattern Recognition And Image Analysis written by Aythami Morales and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-21 with Computers categories.


This 2-volume set constitutes the refereed proceedings of the 9th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2019, held in Madrid, Spain, in July 2019. The 99 papers in these volumes were carefully reviewed and selected from 137 submissions. They are organized in topical sections named: Part I: best ranked papers; machine learning; pattern recognition; image processing and representation. Part II: biometrics; handwriting and document analysis; other applications.



Machine Learning And Deep Learning With Python


Machine Learning And Deep Learning With Python
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Author : James Chen
language : en
Publisher: James Chen
Release Date : 2023-02-07

Machine Learning And Deep Learning With Python written by James Chen and has been published by James Chen this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-07 with Computers categories.


This book is a comprehensive guide to understanding and implementing cutting-edge machine learning and deep learning techniques using Python programming language. Written with both beginners and experienced developers in mind, this book provides a thorough overview of the foundations of machine learning and deep learning, including mathematical fundamentals, optimization algorithms, and neural networks. Starting with the basics of Python programming, this book gradually builds up to more advanced topics, such as artificial neural networks, convolutional neural networks, and generative adversarial networks. Each chapter is filled with clear explanations, practical examples, and step-by-step tutorials that allow readers to gain a deep understanding of the underlying principles of machine learning and deep learning. Throughout the book, readers will also learn how to use popular Python libraries and packages, including numpy, pandas, scikit-learn, TensorFlow, and Keras, to build and train powerful machine learning and deep learning models for a variety of real-world applications, such as regression and classification, K-means, support vector machines, and recommender systems. Whether you are a seasoned data scientist or a beginner looking to enter the world of machine learning, this book is the ultimate resource for mastering these cutting-edge technologies and taking your skills to the next level. High-school level of mathematical knowledge and all levels (including entry-level) of programming skills are good to start, all Python codes are available at Github.com. Table Of Contents 1 Introduction 1.1 Artificial Intelligence, Machine Learning and Deep Learning 1.2 Whom This Book Is For 1.3 How This Book Is Organized 2 Environments 2.1 Source Codes for This Book 2.2 Cloud Environments 2.3 Docker Hosted on Local Machine 2.4 Install on Local Machines 2.5 Install Required Packages 3 Math Fundamentals 3.1 Linear Algebra 3.2 Calculus 3.3 Advanced Functions 4 Machine Learning 4.1 Linear Regression 4.2 Logistic Regression 4.3 Multinomial Logistic Regression 4.4 K-Means Clustering 4.5 Principal Component Analysis (PCA) 4.6 Support Vector Machine (SVM) 4.7 K-Nearest Neighbors 4.8 Anomaly Detection 4.9 Artificial Neural Network (ANN) 4.10 Convolutional Neural Network (CNN) 4.11 Recommendation System 4.12 Generative Adversarial Network References About the Author



Introduction To Scientific Programming With Python


Introduction To Scientific Programming With Python
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Author : Pankaj Jayaraman
language : en
Publisher: Educohack Press
Release Date : 2025-02-20

Introduction To Scientific Programming With Python written by Pankaj Jayaraman and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Computers categories.


"Introduction to Scientific Programming with Python" offers an immersive exploration into the dynamic field of scientific programming using Python. We cater to a diverse audience, serving as an entry point for novices and a valuable resource for seasoned practitioners in scientific computing. Python's popularity in scientific circles stems from its readability, versatility, and extensive libraries for numerical computing, data analysis, and visualization. We cover fundamental programming concepts and gradually introduce advanced techniques specific to scientific applications. From mastering Python basics to exploring advanced topics like machine learning and symbolic mathematics, each chapter provides a structured and hands-on learning experience. Real-world case studies, practical examples, and exercises ensure readers grasp theoretical concepts and gain practical skills. Throughout the book, Python becomes a tool of empowerment, enabling readers to unravel complex scientific data, model intricate phenomena, and contribute meaningfully to their fields. "Introduction to Scientific Programming with Python" is an invaluable companion for harnessing Python's potential in scientific inquiry and discovery. By the end, readers will have a robust foundation in Python and the confidence to apply scientific programming methodologies to real-world problems. This book unlocks the door to a world where Python drives exploration, discovery, and innovation in science.



Cyber Threat Intelligence


Cyber Threat Intelligence
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Author : Ali Dehghantanha
language : en
Publisher: Springer
Release Date : 2018-04-27

Cyber Threat Intelligence written by Ali Dehghantanha and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-27 with Computers categories.


This book provides readers with up-to-date research of emerging cyber threats and defensive mechanisms, which are timely and essential. It covers cyber threat intelligence concepts against a range of threat actors and threat tools (i.e. ransomware) in cutting-edge technologies, i.e., Internet of Things (IoT), Cloud computing and mobile devices. This book also provides the technical information on cyber-threat detection methods required for the researcher and digital forensics experts, in order to build intelligent automated systems to fight against advanced cybercrimes. The ever increasing number of cyber-attacks requires the cyber security and forensic specialists to detect, analyze and defend against the cyber threats in almost real-time, and with such a large number of attacks is not possible without deeply perusing the attack features and taking corresponding intelligent defensive actions – this in essence defines cyber threat intelligence notion. However, such intelligence would not be possible without the aid of artificial intelligence, machine learning and advanced data mining techniques to collect, analyze, and interpret cyber-attack campaigns which is covered in this book. This book will focus on cutting-edge research from both academia and industry, with a particular emphasis on providing wider knowledge of the field, novelty of approaches, combination of tools and so forth to perceive reason, learn and act on a wide range of data collected from different cyber security and forensics solutions. This book introduces the notion of cyber threat intelligence and analytics and presents different attempts in utilizing machine learning and data mining techniques to create threat feeds for a range of consumers. Moreover, this book sheds light on existing and emerging trends in the field which could pave the way for future works. The inter-disciplinary nature of this book, makes it suitable for a wide range of audiences with backgrounds in artificial intelligence, cyber security, forensics, big data and data mining, distributed systems and computer networks. This would include industry professionals, advanced-level students and researchers that work within these related fields.