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Author: Biju Issac
Publisher: CRC Press
ISBN: 1482207060
Category : Computers
Languages : en
Pages : 504
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Book Description
In today’s age of wireless and mobile computing, network and computer security is paramount. Case Studies in Secure Computing: Achievements and Trends gathers the latest research from researchers who share their insights and best practices through illustrative case studies. This book examines the growing security attacks and countermeasures in the stand-alone and networking worlds, along with other pertinent security issues. The many case studies capture a truly wide range of secure computing applications. Surveying the common elements in computer security attacks and defenses, the book: Describes the use of feature selection and fuzzy logic in a decision tree model for intrusion detection Introduces a set of common fuzzy-logic-based security risk estimation techniques with examples Proposes a secure authenticated multiple-key establishment protocol for wireless sensor networks Investigates various malicious activities associated with cloud computing and proposes some countermeasures Examines current and emerging security threats in long-term evolution backhaul and core networks Supplies a brief introduction to application-layer denial-of-service (DoS) attacks Illustrating the security challenges currently facing practitioners, this book presents powerful security solutions proposed by leading researchers in the field. The examination of the various case studies will help to develop the practical understanding required to stay one step ahead of the security threats on the horizon. This book will help those new to the field understand how to mitigate security threats. It will also help established practitioners fine-tune their approach to establishing robust and resilient security for next-generation computing systems.
Author: Biju Issac
Publisher: CRC Press
ISBN: 1482207060
Category : Computers
Languages : en
Pages : 504
Get Book Here
Book Description
In today’s age of wireless and mobile computing, network and computer security is paramount. Case Studies in Secure Computing: Achievements and Trends gathers the latest research from researchers who share their insights and best practices through illustrative case studies. This book examines the growing security attacks and countermeasures in the stand-alone and networking worlds, along with other pertinent security issues. The many case studies capture a truly wide range of secure computing applications. Surveying the common elements in computer security attacks and defenses, the book: Describes the use of feature selection and fuzzy logic in a decision tree model for intrusion detection Introduces a set of common fuzzy-logic-based security risk estimation techniques with examples Proposes a secure authenticated multiple-key establishment protocol for wireless sensor networks Investigates various malicious activities associated with cloud computing and proposes some countermeasures Examines current and emerging security threats in long-term evolution backhaul and core networks Supplies a brief introduction to application-layer denial-of-service (DoS) attacks Illustrating the security challenges currently facing practitioners, this book presents powerful security solutions proposed by leading researchers in the field. The examination of the various case studies will help to develop the practical understanding required to stay one step ahead of the security threats on the horizon. This book will help those new to the field understand how to mitigate security threats. It will also help established practitioners fine-tune their approach to establishing robust and resilient security for next-generation computing systems.
Author: Kashyap, Ramgopal
Publisher: IGI Global
ISBN: 1799801845
Category : Computers
Languages : en
Pages : 318
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Book Description
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: Dr. K. Vijayalakshmi
Publisher: Archers & Elevators Publishing House
ISBN: 9390996309
Category : Antiques & Collectibles
Languages : en
Pages : 198
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Book Description
Author: John D. Kelleher
Publisher: MIT Press
ISBN: 0262361108
Category : Computers
Languages : en
Pages : 853
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Book Description
The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.
Author: Danish Haroon
Publisher: Apress
ISBN: 1484228235
Category : Computers
Languages : en
Pages : 216
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Book Description
Embrace machine learning approaches and Python to enable automatic rendering of rich insights and solve business problems. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on minimal time and resources. Python Machine Learning Case Studies takes you through the steps to improve business processes and determine the pivotal points that frame strategies. You’ll see machine learning techniques that you can use to support your products and services. Moreover you’ll learn the pros and cons of each of the machine learning concepts to help you decide which one best suits your needs. By taking a step-by-step approach to coding in Python you’ll be able to understand the rationale behind model selection and decisions within the machine learning process. The book is equipped with practical examples along with code snippets to ensure that you understand the data science approach to solving real-world problems. What You Will Learn Gain insights into machine learning concepts Work on real-world applications of machine learning Learn concepts of model selection and optimization Get a hands-on overview of Python from a machine learning point of view Who This Book Is For Data scientists, data analysts, artificial intelligence engineers, big data enthusiasts, computer scientists, computer sciences students, and capital market analysts.
Author: Vishal Jain
Publisher: CRC Press
ISBN: 100045567X
Category : Business & Economics
Languages : en
Pages : 295
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Book Description
Technology is moving at an exponential pace in this era of computational intelligence. Machine learning has emerged as one of the most promising tools used to challenge and think beyond current limitations. This handbook will provide readers with a leading edge to improving their products and processes through optimal and smarter machine learning techniques. This handbook focuses on new machine learning developments that can lead to newly developed applications. It uses a predictive and futuristic approach, which makes machine learning a promising tool for processes and sustainable solutions. It also promotes newer algorithms that are more efficient and reliable for new dimensions in discovering other applications, and then goes on to discuss the potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making. Individuals looking for machine learning-based knowledge will find interest in this handbook. The readership ranges from undergraduate students of engineering and allied courses to researchers, professionals, and application designers.
Author: Rashmi Agrawal
Publisher: CRC Press
ISBN: 1000098281
Category : Computers
Languages : en
Pages : 339
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Book Description
The idea behind this book is to simplify the journey of aspiring readers and researchers to understand Big Data, IoT and Machine Learning. It also includes various real-time/offline applications and case studies in the fields of engineering, computer science, information security and cloud computing using modern tools. This book consists of two sections: Section I contains the topics related to Applications of Machine Learning, and Section II addresses issues about Big Data, the Cloud and the Internet of Things. This brings all the related technologies into a single source so that undergraduate and postgraduate students, researchers, academicians and people in industry can easily understand them. Features Addresses the complete data science technologies workflow Explores basic and high-level concepts and services as a manual for those in the industry and at the same time can help beginners to understand both basic and advanced aspects of machine learning Covers data processing and security solutions in IoT and Big Data applications Offers adaptive, robust, scalable and reliable applications to develop solutions for day-to-day problems Presents security issues and data migration techniques of NoSQL databases
Author: Neeraj Kumar
Publisher: CRC Press
ISBN: 1000163490
Category : Computers
Languages : en
Pages : 360
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Book Description
Present book covers new paradigms in Blockchain, Big Data and Machine Learning concepts including applications and case studies. It explains dead fusion in realizing the privacy and security of blockchain based data analytic environment. Recent research of security based on big data, blockchain and machine learning has been explained through actual work by practitioners and researchers, including their technical evaluation and comparison with existing technologies. The theoretical background and experimental case studies related to real-time environment are covered as well. Aimed at Senior undergraduate students, researchers and professionals in computer science and engineering and electrical engineering, this book: Converges Blockchain, Big Data and Machine learning in one volume. Connects Blockchain technologies with the data centric applications such Big data and E-Health. Easy to understand examples on how to create your own blockchain supported by case studies of blockchain in different industries. Covers big data analytics examples using R. Includes lllustrative examples in python for blockchain creation.
Author: Pedro Larrañaga
Publisher: CRC Press
ISBN: 135112837X
Category : Business & Economics
Languages : en
Pages : 349
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Book Description
Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revolution, and provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice. The book introduces the fourth industrial revolution and its current impact on organizations and society. It explores machine learning fundamentals, and includes four case studies that address a real-world problem in the manufacturing or logistics domains, and approaches machine learning solutions from an application-oriented point of view. The book should be of special interest to researchers interested in real-world industrial problems. Features Describes the opportunities, challenges, issues, and trends offered by the fourth industrial revolution Provides a user-friendly introduction to machine learning with examples of cutting-edge applications in different industrial sectors Includes four case studies addressing real-world industrial problems solved with machine learning techniques A dedicated website for the book contains the datasets of the case studies for the reader's reproduction, enabling the groundwork for future problem-solving Uses of three of the most widespread software and programming languages within the engineering and data science communities, namely R, Python, and Weka
Author: Drew Conway
Publisher: "O'Reilly Media, Inc."
ISBN: 1449330533
Category : Computers
Languages : en
Pages : 323
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Book Description
If you’re an experienced programmer interested in crunching data, this book will get you started with machine learning—a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation. Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you’ll learn how to analyze sample datasets and write simple machine learning algorithms. Machine Learning for Hackers is ideal for programmers from any background, including business, government, and academic research. Develop a naïve Bayesian classifier to determine if an email is spam, based only on its text Use linear regression to predict the number of page views for the top 1,000 websites Learn optimization techniques by attempting to break a simple letter cipher Compare and contrast U.S. Senators statistically, based on their voting records Build a “whom to follow” recommendation system from Twitter data
