The success of many companies through the assistance of bitcoin proves that technology continually dominates and transforms how economics operate. However, a deeper, more conceptual understanding of how these technologies work to identify innovation opportunities and how to successfully thrive in an increasingly competitive environment is needed for the entrepreneurs of tomorrow. Transforming Businesses With Bitcoin Mining and Blockchain Applications provides innovative insights into IT infrastructure and emerging trends in the realm of digital business technologies. This publication analyzes and extracts information from Bitcoin networks and provides the necessary steps to designing open blockchain. Highlighting topics that include financial markets, risk management, and smart technologies, the research contained within the title is ideal for entrepreneurs, business professionals, managers, executives, academicians, researchers, and business students.

DESCRIPTION Users expect search to be simple: They enter a few terms and expect perfectly-organized, relevant results instantly. But behind this simple user experience, complex machinery is at work. Whether using Elasticsearch, Solr, or another search technology, the solution is never one size fits all. Returning the right search results requires conveying domain knowledge and business rules in the search engine's data structures, text analytics, and results ranking capabilities. Relevant Search demystifies relevance work. Using Elasticsearch, it tells how to return engaging search results to users, helping readers understand and leverage the internals of Lucene-based search engines. The book walks through several real-world problems using a cohesive philosophy that combines text analysis, query building, and score shaping to express business ranking rules to the search engine. It outlines how to guide the engineering process by monitoring search user behavior and shifting the enterprise to a search-first culture focused on humans, not computers. It also shows how the search engine provides a deeply pluggable platform for integrating search ranking with machine learning, ontologies, personalization, domain-specific expertise, and other enriching sources. KEY FEATURES Highly relevant, concrete, hands-on guide Digs deep into search engine technology Contains essential tools, tips, and strategies for building engaging search engines AUDIENCE For readers who can code moderately complex tasks. ABOUT THE TECHNOLOGY Lucene is the underlying technology that backs both Elasticsearch and Solr. Dominant search engines are based upon Lucene and since Lucene itself is based upon the strong foundation of Information Retrieval research, the book will be applicable to almost any search technology available now or in the foreseeable future.

It is known that trust is of the utmost importance in human interactions, and blockchain technology establishes a new type of foundation for financial and political confidence. This new kind of trust is based on cryptographic techniques and distributed in digital networks. In an uncertain world where it is difficult to tell what is real or fake, decentralized organizational networks may prove to be particularly competitive given that this new ""distributed trust"" endows them with an unusual functional autonomy, namely guaranteeing the authenticity, confidentiality, and integrity of the processed data. Besides the direct sharing of information enabled by blockchain, transactions can now also take place with newfound trust and ways to safely manage personal data. It is important to look at these implications, particularly in sectors such as business and healthcare. Political and Economic Implications of Blockchain Technology in Business and Healthcare provides relevant theoretical frameworks on the political and economic impact of blockchain technology, which is thought to be able to redesign human interactions concerning transactions. Specifically, it will give ideas, concepts, and instruments considered relevant to advance the knowledge about ""cryptoeconomics"" and decentralized governance. The chapters will also provide several insights on business applications of this digital innovation, particularly in the healthcare sector, and will explore the ethical impact of the new ""distributed trust"" paradigm resulting from the surge of such a disruptive technology. This book is essential for students and researchers in social and life sciences, professionals and policymakers working in the fields of public and business administration, healthcare workers and researchers, academicians, and students interested in blockchain technology and the political and economic impacts in the industry.

Multinational organizations have begun to realize that sentiment mining plays an important role for decision making and market strategy. The revolutionary growth of digital marketing not only changes the market game, but also brings forth new opportunities for skilled professionals and expertise. Currently, the technologies are rapidly changing, and artificial intelligence (AI) and machine learning are contributing as game-changing technologies. These are not only trending but are also increasingly popular among data scientists and data analysts. New Opportunities for Sentiment Analysis and Information Processing provides interdisciplinary research in information retrieval and sentiment analysis including studies on extracting sentiments from textual data, sentiment visualization-based dimensionality reduction for multiple features, and deep learning-based multi-domain sentiment extraction. The book also optimizes techniques used for sentiment identification and examines applications of sentiment analysis and emotion detection. Covering such topics as communication networks, natural language processing, and semantic analysis, this book is essential for data scientists, data analysts, IT specialists, scientists, researchers, academicians, and students.

Data Structures and Abstractions with Java is suitable for one- or two-semester courses in data structures (CS-2) in the departments of Computer Science, Computer Engineering, Business, and Management Information Systems. This book is also useful for programmers and software engineers interested in learning more about data structures and abstractions. This is the most student-friendly data structures text available that introduces ADTs in individual, brief chapters - each with pedagogical tools to help students master each concept. Using the latest features of Java, this unique object-oriented presentation makes a clear distinction between specification and implementation to simplify learning, while providing maximum classroom flexibility. Teaching and Learning Experience This book will provide a better teaching and learning experience-for you and your students. It will help: Aid comprehension and facilitate teaching with an approachable format and content organization: Material is organized into small segments that focus a reader's attention and provide greater instructional flexibility. Support learning with student-friendly pedagogy: In-text and online features help students master the material.

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.

This updated compendium provides the linear algebra background necessary to understand and develop linear algebra applications in data mining and machine learning.Basic knowledge and advanced new topics (spectral theory, singular values, decomposition techniques for matrices, tensors and multidimensional arrays) are presented together with several applications of linear algebra (k-means clustering, biplots, least square approximations, dimensionality reduction techniques, tensors and multidimensional arrays).The useful reference text includes more than 600 exercises and supplements, many with completed solutions and MATLAB applications.The volume benefits professionals, academics, researchers and graduate students in the fields of pattern recognition/image analysis, AI, machine learning and databases.

Continual advancements in web technology have highlighted the need for formatted systems that computers can utilize to easily read and sift through the hundreds of thousands of data points across the internet. Therefore, having the most relevant data in the least amount of time to optimize the productivity of users becomes a priority. Semantic Web Science and Real-World Applications provides emerging research exploring the theoretical and practical aspects of semantic web science and real-world applications within the area of big data. Featuring coverage on a broad range of topics such as artificial intelligence, social media monitoring, and microblogging recommendation systems, this book is ideally designed for IT consultants, academics, professionals, and researchers of web science seeking the current developments, requirements and standards, and technology spaces presented across academia and industries.

Learn how to create, train, and tweak large language models (LLMs) by building one from the ground up!

In Build a Large Language Model (from Scratch) bestselling author Sebastian Raschka guides you step by step through creating your own LLM. Each stage is explained with clear text, diagrams, and examples. You’ll go from the initial design and creation, to pretraining on a general corpus, and on to fine-tuning for specific tasks.

Build a Large Language Model (from Scratch) teaches you how to:

• Plan and code all the parts of an LLM
• Prepare a dataset suitable for LLM training
• Fine-tune LLMs for text classification and with your own data
• Use human feedback to ensure your LLM follows instructions
• Load pretrained weights into an LLM

Build a Large Language Model (from Scratch) takes you inside the AI black box to tinker with the internal systems that power generative AI. As you work through each key stage of LLM creation, you’ll develop an in-depth understanding of how LLMs work, their limitations, and their customization methods. Your LLM can be developed on an ordinary laptop, and used as your own personal assistant.