Download or read book Vector Search for Practitioners with Elastic written by Bahaaldine Azarmi and published by Packt Publishing Ltd. This book was released on 2023-11-30 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book delves into the practical applications of vector search in Elastic and embodies a broader philosophy. It underscores the importance of search in the age of Generative Al and Large Language Models. This narrative goes beyond the 'how' to address the 'why' - highlighting our belief in the transformative power of search and our dedication to pushing boundaries to meet and exceed customer expectations." Shay Banon Founder & CTO at Elastic Key Features Install, configure, and optimize the ChatGPT-Elasticsearch plugin with a focus on vector data Learn how to load transformer models, generate vectors, and implement vector search with Elastic Develop a practical understanding of vector search, including a review of current vector databases Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWhile natural language processing (NLP) is largely used in search use cases, this book aims to inspire you to start using vectors to overcome equally important domain challenges like observability and cybersecurity. The chapters focus mainly on integrating vector search with Elastic to enhance not only their search but also observability and cybersecurity capabilities. The book, which also features a foreword written by the founder of Elastic, begins by teaching you about NLP and the functionality of Elastic in NLP processes. Here you’ll delve into resource requirements and find out how vectors are stored in the dense-vector type along with specific page cache requirements for fast response times. As you advance, you’ll discover various tuning techniques and strategies to improve machine learning model deployment, including node scaling, configuration tuning, and load testing with Rally and Python. You’ll also cover techniques for vector search with images, fine-tuning models for improved performance, and the use of clip models for image similarity search in Elasticsearch. Finally, you’ll explore retrieval-augmented generation (RAG) and learn to integrate ChatGPT with Elasticsearch to leverage vectorized data, ELSER's capabilities, and RRF's refined search mechanism. By the end of this NLP book, you’ll have all the necessary skills needed to implement and optimize vector search in your projects with Elastic.What you will learn Optimize performance by harnessing the capabilities of vector search Explore image vector search and its applications Detect and mask personally identifiable information Implement log prediction for next-generation observability Use vector-based bot detection for cybersecurity Visualize the vector space and explore Search.Next with Elastic Implement a RAG-enhanced application using Streamlit Who this book is for If you're a data professional with experience in Elastic observability, search, or cybersecurity and are looking to expand your knowledge of vector search, this book is for you. This book provides practical knowledge useful for search application owners, product managers, observability platform owners, and security operations center professionals. Experience in Python, using machine learning models, and data management will help you get the most out of this book.

Download or read book Elastic Stack 8 x Cookbook written by Huage Chen and published by Packt Publishing Ltd. This book was released on 2024-06-28 with total page 688 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the full potential of Elastic Stack for search, analytics, security, and observability and manage substantial data workloads in both on-premise and cloud environments Key Features Explore the diverse capabilities of the Elastic Stack through a comprehensive set of recipes Build search applications, analyze your data, and observe cloud-native applications Harness powerful machine learning and AI features to create data science and search applications Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionLearn how to make the most of the Elastic Stack (ELK Stack) products—including Elasticsearch, Kibana, Elastic Agent, and Logstash—to take data reliably and securely from any source, in any format, and then search, analyze, and visualize it in real-time. This cookbook takes a practical approach to unlocking the full potential of Elastic Stack through detailed recipes step by step. Starting with installing and ingesting data using Elastic Agent and Beats, this book guides you through data transformation and enrichment with various Elastic components and explores the latest advancements in search applications, including semantic search and Generative AI. You'll then visualize and explore your data and create dashboards using Kibana. As you progress, you'll advance your skills with machine learning for data science, get to grips with natural language processing, and discover the power of vector search. The book covers Elastic Observability use cases for log, infrastructure, and synthetics monitoring, along with essential strategies for securing the Elastic Stack. Finally, you'll gain expertise in Elastic Stack operations to effectively monitor and manage your system.What you will learn Discover techniques for collecting data from diverse sources Visualize data and create dashboards using Kibana to extract business insights Explore machine learning, vector search, and AI capabilities of Elastic Stack Handle data transformation and data formatting Build search solutions from the ingested data Leverage data science tools for in-depth data exploration Monitor and manage your system with Elastic Stack Who this book is for This book is for Elastic Stack users, developers, observability practitioners, and data professionals ranging from beginner to expert level. If you’re a developer, you’ll benefit from the easy-to-follow recipes for using APIs and features to build powerful applications, and if you’re an observability practitioner, this book will help you with use cases covering APM, Kubernetes, and cloud monitoring. For data engineers and AI enthusiasts, the book covers dedicated recipes on vector search and machine learning. No prior knowledge of the Elastic Stack is required.

Download or read book Getting Started with DuckDB written by Simon Aubury and published by Packt Publishing Ltd. This book was released on 2024-06-24 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analyze and transform data efficiently with DuckDB, a versatile, modern, in-process SQL database Key Features Use DuckDB to rapidly load, transform, and query data across a range of sources and formats Gain practical experience using SQL, Python, and R to effectively analyze data Learn how open source tools and cloud services in the broader data ecosystem complement DuckDB’s versatile capabilities Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDuckDB is a fast in-process analytical database. Getting Started with DuckDB offers a practical overview of its usage. You'll learn to load, transform, and query various data formats, including CSV, JSON, and Parquet. The book covers DuckDB's optimizations, SQL enhancements, and extensions for specialized applications. Working with examples in SQL, Python, and R, you'll explore analyzing public datasets and discover tools enhancing DuckDB workflows. This guide suits both experienced and new data practitioners, quickly equipping you to apply DuckDB's capabilities in analytical projects. You'll gain proficiency in using DuckDB for diverse tasks, enabling effective integration into your data workflows.What you will learn Understand the properties and applications of a columnar in-process database Use SQL to load, transform, and query a range of data formats Discover DuckDB's rich extensions and learn how to apply them Use nested data types to model semi-structured data and extract and model JSON data Integrate DuckDB into your Python and R analytical workflows Effectively leverage DuckDB's convenient SQL enhancements Explore the wider ecosystem and pathways for building DuckDB-powered data applications Who this book is for If you’re interested in expanding your analytical toolkit, this book is for you. It will be particularly valuable for data analysts wanting to rapidly explore and query complex data, data and software engineers looking for a lean and versatile data processing tool, along with data scientists needing a scalable data manipulation library that integrates seamlessly with Python and R. You will get the most from this book if you have some familiarity with SQL and foundational database concepts, as well as exposure to a programming language such as Python or R.

Download or read book Elasticsearch The Definitive Guide written by Clinton Gormley and published by "O'Reilly Media, Inc.". This book was released on 2015-01-23 with total page 659 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whether you need full-text search or real-time analytics of structured data—or both—the Elasticsearch distributed search engine is an ideal way to put your data to work. This practical guide not only shows you how to search, analyze, and explore data with Elasticsearch, but also helps you deal with the complexities of human language, geolocation, and relationships. If you’re a newcomer to both search and distributed systems, you’ll quickly learn how to integrate Elasticsearch into your application. More experienced users will pick up lots of advanced techniques. Throughout the book, you’ll follow a problem-based approach to learn why, when, and how to use Elasticsearch features. Understand how Elasticsearch interprets data in your documents Index and query your data to take advantage of search concepts such as relevance and word proximity Handle human language through the effective use of analyzers and queries Summarize and group data to show overall trends, with aggregations and analytics Use geo-points and geo-shapes—Elasticsearch’s approaches to geolocation Model your data to take advantage of Elasticsearch’s horizontal scalability Learn how to configure and monitor your cluster in production

Download or read book Cisco TelePresence Fundamentals written by Tim Szigeti and published by Cisco Press. This book was released on 2009-05-26 with total page 819 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cisco TelePresenceTM Systems (CTS) create live, face-to-face meeting experiences, providing a breakthrough virtual conferencing and collaboration experience that transcends anything previously achievable by videoconferencing. Although the business case for deploying CTS is compelling, implementing it requires advanced knowledge of the latest networking technologies, an attention to detail, and thorough planning. In this book, four leading CTS technical experts cover everything you need to know to successfully design and deploy CTS in your environment. The authors cover every element of a working CTS solution: video, audio, signaling protocols and call processing, LAN and WAN design, multipoint, security, inter-company connectivity, and much more. They deliver start-to-finish coverage of CTS design for superior availability, QoS support, and security in converged networks. They also present the first chapter-length design guide of it’s kind detailing the room requirements and recommendations for lighting, acoustics, and ambience within various types of TelePresence rooms. Cisco Telepresence Fundamentals is an indispensable resource for all technical professionals tasked with deploying CTS, including netadmins, sysadmins, audio/video specialists, VoIP specialists, and operations staff. This is the only book that: Introduces every component of a complete CTS solution and shows how they work together Walks through connecting CTS in real-world environments Demonstrates how to secure virtual meetings using Cisco firewalls and security protocols Includes a full chapter on effective TelePresence room design Walks through every aspect of SIP call signaling design, including both single-cluster and intercluster examples for use in a TelePresence environment Provides prequalification, room, and network path assessment considerations to help you anticipate and avoid problems Tim Szigeti, CCIE® No. 9794, technical leader within the Cisco® Enterprise Systems Engineering team, is responsible for defining Cisco TelePresence network deployment best practices. He also coauthored the Cisco Press book End-to-End QoS Network Design. Kevin McMenamy, senior manager of technical marketing in the Cisco TelePresence Systems Business Unit, has spent the past nine years at Cisco supporting IP videoconferencing, video telephony, and unified communications. Roland Saville, technical leader for the Cisco Enterprise Systems Engineering team, tests and develops best-practice design guides for Cisco TelePresence enterprise deployments. Alan Glowacki is a Cisco technical marketing engineer responsible for supporting Cisco TelePresence customers and sales teams. Use Cisco TelePresence Systems (CTS) to enhance global teamwork and collaboration, both within your own enterprise and with your customers, partners, and vendors Understand how the various components of the Cisco TelePresence Solution connect and work together Integrate CTS into existing LAN, enterprise, and service provider networks Successfully design and deploy a global TelePresence network Understand the importance of room dimensions, acoustics, lighting, and ambience and how to properly design the physical room environment Provide the high levels of network availability CTS requires Leverage the Cisco quality of service (QoS) tools most relevant to CTS network provisioning and deployment Systematically secure CTS using TLS, dTLS, sRTP, SSH, and Cisco firewalls This book is part of the Cisco Press® Fundamentals Series. Books in this series introduce networking professionals to new networking technologies, covering network topologies, sample deployment concepts, protocols, and management techniques. Category: IP Communications Covers: Cisco TelePresence Systems

Download or read book The Hundred page Machine Learning Book written by Andriy Burkov and published by . This book was released on 2019 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a practical guide to get started and execute on machine learning within a few days without necessarily knowing much about machine learning.The first five chapters are enough to get you started and the next few chapters provide you a good feel of more advanced topics to pursue.

Download or read book Orthodontic Treatment of the Class II Noncompliant Patient written by Moschos A. Papadopoulos and published by Elsevier Health Sciences. This book was released on 2006-01-01 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: Section I CLASS II ORTHODONTIC TREATMENT AND COMPLIANCE 1. The problem of compliance in orthodontics 2. Classification of the non-compliance appliances used for Class II correction Section II NTER-MAXILLARY APPLIANCES USED FOR THE MANAGEMENT OF CLASS II NON-COMPLIANT PATIENTS 3. Overview of the inter-maxillary non-compliance appliances 4. The Herbst appliance 5. The Cantilever Bite Jumper 6. The Ritto Appliance(R) 7. The Mandibular Protraction 8. The Mandibular Anterior Repositioning Appliance 9. Energy management: The philosophy behind fixed intermaxillary mechanics 10. The Jasper Jumper 11. The Flex Developer 12. The Eureka Spring 13. The Twin Force Bite Corrector in the correction of Class II malocclusion in adolescent patients 14. The Sabbagh Universal Spring Section III INTRA-MAXILLARY DISTALIZATION APPLIANCES USED FOR THE MANAGEMENT OF CLASS II NON-COMPLIANT PATIENTS 15. Overview of the intra-maxillary non-compliance distalization appliances 16. The Pendulum appliance 17. The Penguin Pendulum 18. Non-compliance Class II treatment with the Distal JetAldo Carano 19. The Keles Slider appliance for bilateral and unilateral maxillary molar distalization 20. The Jones Jig and modifications 21. The use of magnets for maxillary molar distalization 22. The First Class appliance 23. An effective and precise method for rapid molar derotation Section IV INTRA-MAXILLARY APPLIANCES WITH ABSOLUTE ANCHORAGE USED FOR THE MANAGEMENT OF CLASS II MALOCCLUSION 24. Overview of the intra-maxillary non-compliance appliances with absolute anchorage 25. The use of implants as absolute anchorage for Class II correction 26. The use of onplants for maxillary molar distalization Section V CLINICAL EFFICACY OF THE NON-COMPLIANCE APPLIANCES 27. Clinical efficacy of the non-compliance appliances used for Class II orthodontic correction.

Download or read book Elasticsearch in Action written by Roy Russo and published by Simon and Schuster. This book was released on 2015-11-17 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Elasticsearch in Action teaches you how to build scalable search applications using Elasticsearch. You'll ramp up fast, with an informative overview and an engaging introductory example. Within the first few chapters, you'll pick up the core concepts you need to implement basic searches and efficient indexing. With the fundamentals well in hand, you'll go on to gain an organized view of how to optimize your design. Perfect for developers and administrators building and managing search-oriented applications. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Modern search seems like magic—you type a few words and the search engine appears to know what you want. With the Elasticsearch real-time search and analytics engine, you can give your users this magical experience without having to do complex low-level programming or understand advanced data science algorithms. You just install it, tweak it, and get on with your work. About the Book Elasticsearch in Action teaches you how to write applications that deliver professional quality search. As you read, you'll learn to add basic search features to any application, enhance search results with predictive analysis and relevancy ranking, and use saved data from prior searches to give users a custom experience. This practical book focuses on Elasticsearch's REST API via HTTP. Code snippets are written mostly in bash using cURL, so they're easily translatable to other languages. What's Inside What is a great search application? Building scalable search solutions Using Elasticsearch with any language Configuration and tuning About the Reader For developers and administrators building and managing search-oriented applications. About the Authors Radu Gheorghe is a search consultant and software engineer. Matthew Lee Hinman develops highly available, cloud-based systems. Roy Russo is a specialist in predictive analytics. Table of Contents PART 1 CORE ELASTICSEARCH FUNCTIONALITY Introducing Elasticsearch Diving into the functionality Indexing, updating, and deleting data Searching your data Analyzing your data Searching with relevancy Exploring your data with aggregations Relations among documents PART 2 ADVANCED ELASTICSEARCH FUNCTIONALITY Scaling out Improving performance Administering your cluster

Download or read book Machine Learning with the Elastic Stack Second Edition written by Rich Collier and published by . This book was released on 2021-05-28 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover expert techniques for combining machine learning with the analytic capabilities of Elastic Stack and uncover actionable insights from your data Key Features: Integrate machine learning with distributed search and analytics Preprocess and analyze large volumes of search data effortlessly Operationalize machine learning in a scalable, production-worthy way Book Description: Elastic Stack, previously known as the ELK stack, is a log analysis solution that helps users ingest, process, and analyze search data effectively. With the addition of machine learning, a key commercial feature, the Elastic Stack makes this process even more efficient. This updated second edition of Machine Learning with the Elastic Stack provides a comprehensive overview of Elastic Stack's machine learning features for both time series data analysis as well as for classification, regression, and outlier detection. The book starts by explaining machine learning concepts in an intuitive way. You'll then perform time series analysis on different types of data, such as log files, network flows, application metrics, and financial data. As you progress through the chapters, you'll deploy machine learning within Elastic Stack for logging, security, and metrics. Finally, you'll discover how data frame analysis opens up a whole new set of use cases that machine learning can help you with. By the end of this Elastic Stack book, you'll have hands-on machine learning and Elastic Stack experience, along with the knowledge you need to incorporate machine learning in your distributed search and data analysis platform. What You Will Learn: Find out how to enable the ML commercial feature in the Elastic Stack Understand how Elastic machine learning is used to detect different types of anomalies and make predictions Apply effective anomaly detection to IT operations, security analytics, and other use cases Utilize the results of Elastic ML in custom views, dashboards, and proactive alerting Train and deploy supervised machine learning models for real-time inference Discover various tips and tricks to get the most out of Elastic machine learning Who this book is for: If you're a data professional looking to gain insights into Elasticsearch data without having to rely on a machine learning specialist or custom development, then this Elastic Stack machine learning book is for you. You'll also find this book useful if you want to integrate machine learning with your observability, security, and analytics applications. Working knowledge of the Elastic Stack is needed to get the most out of this book.

Download or read book Nearest Neighbor Search written by Apostolos N. Papadopoulos and published by Springer Science & Business Media. This book was released on 2006-11-22 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern applications are both data and computationally intensive and require the storage and manipulation of voluminous traditional (alphanumeric) and nontraditional data sets (images, text, geometric objects, time-series). Examples of such emerging application domains are: Geographical Information Systems (GIS), Multimedia Information Systems, CAD/CAM, Time-Series Analysis, Medical Information Sstems, On-Line Analytical Processing (OLAP), and Data Mining. These applications pose diverse requirements with respect to the information and the operations that need to be supported. From the database perspective, new techniques and tools therefore need to be developed towards increased processing efficiency. This monograph explores the way spatial database management systems aim at supporting queries that involve the space characteristics of the underlying data, and discusses query processing techniques for nearest neighbor queries. It provides both basic concepts and state-of-the-art results in spatial databases and parallel processing research, and studies numerous applications of nearest neighbor queries.

Download or read book Relevant Search written by John Berryman and published by Simon and Schuster. This book was released on 2016-06-19 with total page 517 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Relevant Search demystifies relevance work. Using Elasticsearch, it teaches you how to return engaging search results to your users, helping you understand and leverage the internals of Lucene-based search engines. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Users are accustomed to and expect instant, relevant search results. To achieve this, you must master the search engine. Yet for many developers, relevance ranking is mysterious or confusing. About the Book Relevant Search demystifies the subject and shows you that a search engine is a programmable relevance framework. You'll learn how to apply Elasticsearch or Solr to your business's unique ranking problems. The book demonstrates how to program relevance and how to incorporate secondary data sources, taxonomies, text analytics, and personalization. In practice, a relevance framework requires softer skills as well, such as collaborating with stakeholders to discover the right relevance requirements for your business. By the end, you'll be able to achieve a virtuous cycle of provable, measurable relevance improvements over a search product's lifetime. What's Inside Techniques for debugging relevance? Applying search engine features to real problems? Using the user interface to guide searchers? A systematic approach to relevance? A business culture focused on improving search About the Reader For developers trying to build smarter search with Elasticsearch or Solr. About the Authors Doug Turnbull is lead relevance consultant at OpenSource Connections, where he frequently speaks and blogs. John Berryman is a data engineer at Eventbrite, where he specializes in recommendations and search. Foreword author, Trey Grainger, is a director of engineering at CareerBuilder and author of Solr in Action. Table of Contents The search relevance problem Search under the hood Debugging your first relevance problem Taming tokens Basic multifield search Term-centric search Shaping the relevance function Providing relevance feedback Designing a relevance-focused search application The relevance-centered enterprise Semantic and personalized search

Download or read book An Introduction to Composite Materials written by D. Hull and published by Cambridge University Press. This book was released on 1996-08-13 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edition has been greatly enlarged and updated to provide both scientists and engineers with a clear and comprehensive understanding of composite materials. In describing both theoretical and practical aspects of their production, properties and usage, the book crosses the borders of many disciplines. Topics covered include: fibres, matrices, laminates and interfaces; elastic deformation, stress and strain, strength, fatigue crack propagation and creep resistance; toughness and thermal properties; fatigue and deterioration under environmental conditions; fabrication and applications. Coverage has been increased to include polymeric, metallic and ceramic matrices and reinforcement in the form of long fibres, short fibres and particles. Designed primarily as a teaching text for final-year undergraduates in materials science and engineering, this book will also interest undergraduates and postgraduates in chemistry, physics, and mechanical engineering. In addition, it will be an excellent source book for academic and technological researchers on materials.

Download or read book Machine Learning with the Elastic Stack written by Rich Collier and published by Packt Publishing Ltd. This book was released on 2019-01-31 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage Elastic Stack’s machine learning features to gain valuable insight from your data Key FeaturesCombine machine learning with the analytic capabilities of Elastic StackAnalyze large volumes of search data and gain actionable insight from themUse external analytical tools with your Elastic Stack to improve its performanceBook Description Machine Learning with the Elastic Stack is a comprehensive overview of the embedded commercial features of anomaly detection and forecasting. The book starts with installing and setting up Elastic Stack. You will perform time series analysis on varied kinds of data, such as log files, network flows, application metrics, and financial data. As you progress through the chapters, you will deploy machine learning within the Elastic Stack for logging, security, and metrics. In the concluding chapters, you will see how machine learning jobs can be automatically distributed and managed across the Elasticsearch cluster and made resilient to failure. By the end of this book, you will understand the performance aspects of incorporating machine learning within the Elastic ecosystem and create anomaly detection jobs and view results from Kibana directly. What you will learnInstall the Elastic Stack to use machine learning featuresUnderstand how Elastic machine learning is used to detect a variety of anomaly typesApply effective anomaly detection to IT operations and security analyticsLeverage the output of Elastic machine learning in custom views, dashboards, and proactive alertingCombine your created jobs to correlate anomalies of different layers of infrastructureLearn various tips and tricks to get the most out of Elastic machine learningWho this book is for If you are a data professional eager to gain insight on Elasticsearch data without having to rely on a machine learning specialist or custom development, Machine Learning with the Elastic Stack is for you. Those looking to integrate machine learning within their search and analytics applications will also find this book very useful. Prior experience with the Elastic Stack is needed to get the most out of this book.

Download or read book Hands On Machine Learning with Scikit Learn Keras and TensorFlow written by Aurélien Géron and published by "O'Reilly Media, Inc.". This book was released on 2019-09-05 with total page 851 pages. Available in PDF, EPUB and Kindle. Book excerpt: Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets

Download or read book Machine Learning written by Maria Johnsen and published by Maria Johnsen. This book was released on 2024-07-06 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning has revolutionized industries, from healthcare to entertainment, by enhancing how we understand and interact with data. Despite its prevalence, mastering this field requires both theoretical knowledge and practical skills. This book bridges that gap, starting with foundational concepts and essential mathematics, then advancing through a wide range of algorithms and techniques. It covers supervised and unsupervised learning, neural networks, deep learning, and reinforcement learning, with clear explanations and practical examples. Real-world applications are highlighted through scenarios and case studies, demonstrating how to solve specific problems with machine learning. You'll find hands-on guides to popular tools and libraries like Python, Scikit-Learn, TensorFlow, Keras, and PyTorch, enabling you to build, evaluate, and deploy models effectively. The book explores cutting-edge topics like quantum machine learning and explainable AI, keeping you updated on the latest trends. Detailed case studies and capstone projects provide practical experience, guiding you through the entire machine learning process. This book, a labor of love born from extensive research and passion, aims to make machine learning accessible and engaging. Machine learning is about curiosity, creativity, and the pursuit of knowledge. Explore, experiment, and enjoy the journey. Thank you for choosing this book. I am excited to be part of your machine learning adventure and look forward to the incredible things you will achieve.

Download or read book Text Analytics with Python written by Dipanjan Sarkar and published by Apress. This book was released on 2016-11-30 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: Derive useful insights from your data using Python. You will learn both basic and advanced concepts, including text and language syntax, structure, and semantics. You will focus on algorithms and techniques, such as text classification, clustering, topic modeling, and text summarization. Text Analytics with Python teaches you the techniques related to natural language processing and text analytics, and you will gain the skills to know which technique is best suited to solve a particular problem. You will look at each technique and algorithm with both a bird's eye view to understand how it can be used as well as with a microscopic view to understand the mathematical concepts and to implement them to solve your own problems. What You Will Learn: Understand the major concepts and techniques of natural language processing (NLP) and text analytics, including syntax and structure Build a text classification system to categorize news articles, analyze app or game reviews using topic modeling and text summarization, and cluster popular movie synopses and analyze the sentiment of movie reviews Implement Python and popular open source libraries in NLP and text analytics, such as the natural language toolkit (nltk), gensim, scikit-learn, spaCy and Pattern Who This Book Is For : IT professionals, analysts, developers, linguistic experts, data scientists, and anyone with a keen interest in linguistics, analytics, and generating insights from textual data

Download or read book Research Handbook on Law and Technology written by Bartosz Brożek and published by Edward Elgar Publishing. This book was released on 2023-12-11 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thorough and incisive Research Handbook reconstructs the scholarly discourses surrounding the field of law and technology, discussing the salient legal, governance and societal problems stemming from the use of different technologies, and how they should be treated under various legal frameworks. This title contains one or more Open Access chapters.