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Advanced Techniques For Using AI to Master Crypto Chapter 1: Introduction to Cryptocurrency Introduction to Cryptocurrency Cryptocurrency has emerged as one of the most revolutionary financial innovations of the 21st century. At its core, cryptocurrency represents digital or virtual currencies that rely on cryptographic principles to secure transactions, regulate issuance, and authenticate transfer of assets. Established in 2009 with the introduction of Bitcoin by an enigmatic figure known as Satoshi Nakamoto, cryptocurrency has since evolved into a multifaceted domain encompassing various aspects of finance and technology. Cryptocurrency owes its existence to the failure and limitations of traditional financial systems. In 2008, the financial crisis exposed the inherent vulnerabilities of centralized banking and the mistrust surrounding monetary institutions. It was against this backdrop that Bitcoin, the first decentralized cryptocurrency, was conceived. By implementing blockchain technology, Bitcoin established the foundation for a new kind of currency free from the control of central authorities and immune to the pitfalls of traditional financial institutions. The impact of cryptocurrencies on modern financial systems cannot be overstated. Cryptocurrencies facilitate peer-to-peer transactions independent of intermediaries, bringing about cost efficiency and speed in transferring funds. As the public becomes increasingly aware of the benefits and potential of cryptocurrencies, the landscape of global finance is undergoing a transformative shift, heralding the advent of a decentralized economy.
In the evolving landscape of Web3, the use of advanced machine learning, artificial intelligence, and cybersecurity transforms industries through theoretical exploration and practical application. The integration of advanced machine learning and AI techniques promises enhanced security protocols, predictive analytics, and adaptive defenses against the increasing number of cyber threats. However, these technological improvements also raise questions regarding privacy, transparency, and the ethical implications of AI-driven security measures. Advanced Machine Learning, AI, and Cybersecurity in Web3: Theoretical Knowledge and Practical Application explores theories and applications of improved technological techniques in Web 3.0. It addresses the challenges inherent to decentralization while harnessing the benefits offered by advances, thereby paving the way for a safer and more advanced digital era. Covering topics such as fraud detection, cryptocurrency, and data management, this book is a useful resource for computer engineers, financial institutions, security and IT professionals, business owners, researchers, scientists, and academicians.
In the landscape of e-commerce, data security has become a concern as businesses navigate the complexities of sensitive customer information protection and cyber threat mitigation. Strategies involving cloud computing, blockchain technology, artificial intelligence, and machine learning offer solutions to strengthen data security and ensure transactional integrity. Implementing these technologies requires a balance of innovation and efficient security protocols. The development and adoption of security strategies is necessary to positively integrate cutting-edge technologies for effective security in online business. Strategies for E-Commerce Data Security: Cloud, Blockchain, AI, and Machine Learning addresses the need for advanced security measures, while examining the current state of e-commerce data security. It explores strategies such as cloud computing, blockchain, artificial intelligence, and machine learning. This book covers topics such as cybersecurity, cloud technology, and forensics, and is a useful resource for computer engineers, business owners, security professionals, government officials, academicians, scientists, and researchers.
Learn how to use AI and blockchain to build decentralized intelligent applications (DIApps) that overcome real-world challenges Key FeaturesUnderstand the fundamental concepts for converging artificial intelligence and blockchainApply your learnings to build apps using machine learning with Ethereum, IPFS, and MoiBitGet well-versed with the AI-blockchain ecosystem to develop your own DIAppsBook Description AI and blockchain are two emerging technologies catalyzing the pace of enterprise innovation. With this book, you’ll understand both technologies and converge them to solve real-world challenges. This AI blockchain book is divided into three sections. The first section covers the fundamentals of blockchain, AI, and affiliated technologies, where you’ll learn to differentiate between the various implementations of blockchains and AI with the help of examples. The second section takes you through domain-specific applications of AI and blockchain. You’ll understand the basics of decentralized databases and file systems and connect the dots between AI and blockchain before exploring products and solutions that use them together. You’ll then discover applications of AI techniques in crypto trading. In the third section, you’ll be introduced to the DIApp design pattern and compare it with the DApp design pattern. The book also highlights unique aspects of SDLC (software development lifecycle) when building a DIApp, shows you how to implement a sample contact tracing application, and delves into the future of AI with blockchain. By the end of this book, you’ll have developed the skills you need to converge AI and blockchain technologies to build smart solutions using the DIApp design pattern. What you will learnGet well-versed in blockchain basics and AI methodologiesUnderstand the significance of data collection and cleaning in AI modelingDiscover the application of analytics in cryptocurrency tradingGet to grips with open, permissioned, and private blockchainsExplore the DIApp design pattern and its merit in digital solutionsFind out how LSTM and ARIMA can be applied in crypto tradingUse the DIApp design pattern to build a sample contact tracing applicationGet started with building your own DIApps across various domainsWho this book is for This book is for blockchain and AI architects, developers, data scientists, data engineers, and evangelists who want to harness the power of artificial intelligence in blockchain applications. If you are looking for a blend of theoretical and practical use cases to understand how to implement smart cognitive insights into blockchain solutions, this book is what you need! Knowledge of machine learning and blockchain concepts is required.
Emerging technologies have become both crucibles and showrooms for the practical application of artificial intelligence, the internet of things, and cloud computing, and for integrating big data into everyday life. Is the digital world optimized and sustainable using intelligence systems, machine learning, and cyber security methods? This complex concoction of challenges requires new thinking of the synergistic utilization of intelligence systems, machine learning, deep learning and blockchain methods, data-driven decision-making with automation infrastructure, autonomous transportation, and connected buildings. Effective AI, Blockchain, and E-Governance Applications for Knowledge Discovery and Management provides a global perspective on current and future trends concerning the integration of intelligent systems with cybersecurity applications, including recent advances and challenges related to the concerns of security and privacy issues in deep learning with an emphasis on the current state-of-the-art methods, methodologies and implementation, attacks, and countermeasures. The book also discusses the challenges that need to be addressed for implementing DL-based security mechanisms that should have the capability of collecting or distributing data across several applications. Topics covered include skill development and tools for intelligence systems, deep learning, machine learning, blockchain, IoT, cloud computing, data ethics, and infrastructure. It is ideal for independent researchers, research scholars, scientists, libraries, industry experts, academic students, business associations, communication and marketing agencies, entrepreneurs, and all potential audiences with a specific interest in these topics.
Survive and thrive amongst the professional traders using sophisticated cryptocurrency analysis and trading techniques The purpose of this book is to provide a concise yet comprehensive background of some effective methods for analyzing markets and creating fully automated AI-optimized trading systems. The book outlines some easy-to-replicate yet highly effective quant trading techniques that can be used for analyzing asset prices and then apply them to Bitcoin prices, showing how to generate actionable insights from data that can be used to create fully automated trading signals and systems. Big data analytics can be enhanced with artificial intelligence techniques. Back testing and optimization methods are presented with a special emphasis placed on the use of distributed genetic algorithms for parameter optimization. Finally, a case study of a fully automated trend-following trading strategy that leverages artificial intelligence is presented. Bitcoin AlphaBotTM combines human insight with AI-driven optimization to build profit table trend trading strategies.
There is now a plethora of internet of things (IoT) devices on the market that can connect to the internet and the desired environment to produce sufficient and reliable data that is required by the government administration for a variety of purposes. Additionally, the potential benefits of incorporating artificial intelligence (AI) and machine learning into governance are numerous. Governments can use AI and machine learning to enforce the law, detect fraud, and monitor urban areas by identifying problems before they occur. The government can also use AI to easily automate processes and replace mundane and repetitive tasks. AI, IoT, and Blockchain Breakthroughs in E-Governance defines and emphasizes various AI algorithms as well as new internet of things and blockchain breakthroughs in the field of e-governance. Covering key topics such as machine learning, government, and artificial intelligence, this premier reference source is ideal for government officials, policymakers, researchers, academicians, practitioners, scholars, instructors, and students.
The book uniquely explores the fundamentals of blockchain and digital twin and their uses in smart hospitals. Artificial Intelligence-Enabled Blockchain Technology and Digital Twin for Smart Hospitals provides fundamental information on blockchain and digital twin technology as effective solutions in smart hospitals. Digital twin technology enables the creation of real-time virtual replicas of hospital assets and patients, enhancing predictive maintenance, operational efficiency, and patient care. Blockchain technology provides a secure and transparent platform for managing and sharing sensitive data, such as medical records and pharmaceutical supply chains. By combining these technologies, smart hospitals can ensure data security, interoperability, and streamlined operations while providing patient-centered care. The book also explores the impact of collected medical data from real-time systems in smart hospitals, and by making it accessible to all doctors via a smartphone or mobile device for fast decisions. Inevitable challenges such as privacy concerns and integration costs must, of course, be addressed. However, the potential benefits in terms of improved healthcare quality, reduced costs, and global health initiatives makes the integration of these technologies a compelling avenue for the future of healthcare. Some of the topics that readers will find in this book include: Wireless Medical Sensor Networks in Smart Hospitals ● DNA Computing in Cryptography ● Enhancing Diabetic Retinopathy and Glaucoma Diagnosis through Efficient Retinal Vessel Segmentation and Disease Classification ● Machine Learning-Enabled Digital Twins for Diagnostic And Therapeutic Purposes ● Blockchain as the Backbone of a Connected Ecosystem of Smart Hospitals ● Blockchain for Edge Association in Digital Twin Empowered 6G Networks ● Blockchain for Security and Privacy in Smart Healthcare ● Blockchain-Enabled Internet of Things (IoTs) Platforms for IoT-Based Healthcare and Biomedical Sector ● Electronic Health Records in a Blockchain ● PSO-Based Hybrid Cardiovascular Disease Prediction for Using Artificial Flora Algorithm ● AI and Transfer Learning Based Framework for Efficient Classification And Detection Of Lyme Disease ● Framework for Gender Detection Using Facial Countenances ● Smartphone-Based Sensors for Biomedical Applications ● Blockchain for Improving Security and Privacy in the Smart Sensor Network ● Sensors and Digital Twin Application in Healthcare Facilities Management ● Integration of Internet of Medical Things (IoMT) with Blockchain Technology to Improve Security and Privacy ● Machine Learning-Driven Digital Twins for Precise Brain Tumor and Breast Cancer Assessment ● Ethical and Technological Convergence: AI and Blockchain in Halal Healthcare ● Digital Twin Application in Healthcare Facilities Management ● Cloud-based Digital Twinning for Structural Health Monitoring Using Deep Learning. Audience The book will be read by hospital and healthcare providers, administrators, policymakers, scientists and engineers in artificial intelligence, information technology, electronics engineering, and related disciplines.
The amalgamation of artificial intelligence (AI), optimization techniques, and blockchain is revolutionizing how to conceptualize, design, and operate aerospace systems. While optimization techniques are pivotal in streamlining aerospace processes, security challenges have recently surfaced. AI and Blockchain Optimization Techniques in Aerospace Engineering delves into the transformative impact of technologies on various facets of the aerospace industry, offering a multidimensional solution to overcome security concerns and enhance the overall efficiency of aerospace systems The book explores how machine learning reshapes aerospace systems by automating complex tasks through self/reinforced learning methods. From air traffic data analysis to flight scheduling, geographical information, and navigation, machine learning has become an indispensable tool, offering valuable insights that enhance aerospace operations. Simultaneously, blockchain technology, with its inherent characteristics of decentralization and tamper-proof ledgers, ensures transparency, accountability, and security in transactions, providing an innovative approach to data integrity and system resilience. Designed for technology development professionals, academicians, data scientists, industrial experts, researchers, and students, the book offers a panoramic view of the latest innovations in the field.
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