Biznes IT
J. Ashley Hunt
The CompTIA Project+ exam is designed for IT professionals who want to improve their career trajectory by gaining certification in project management specific to their industry. This guide covers everything necessary to pass the current iteration of the Project+ PK0-004 exam.The CompTIA Project+ Certification Guide starts by covering project initiation best practices, including an understanding of organizational structures, team roles, and responsibilities. You’ll then study best practices for developing a project charter and the scope of work to produce deliverables necessary to obtain formal approval of the end result. The ability to monitor your project work and make changes as necessary to bring performance back in line with the plan is the difference between a successful and unsuccessful project. The concluding chapters of the book provide best practices to help keep an eye on your projects and close them out successfully. The guide also includes practice questions created to mirror the exam experience and help solidify your understanding of core project management concepts.By the end of this book, you will be able to develop creative solutions for complex issues faced in project management.
J. Ashley Hunt
The CompTIA Project+ exam is designed for IT professionals who want to improve their career trajectory by gaining certification in project management specific to their industry. This guide covers everything necessary to pass the current iteration of the Project+ PK0-004 exam.The CompTIA Project+ Certification Guide starts by covering project initiation best practices, including an understanding of organizational structures, team roles, and responsibilities. You’ll then study best practices for developing a project charter and the scope of work to produce deliverables necessary to obtain formal approval of the end result. The ability to monitor your project work and make changes as necessary to bring performance back in line with the plan is the difference between a successful and unsuccessful project. The concluding chapters of the book provide best practices to help keep an eye on your projects and close them out successfully. The guide also includes practice questions created to mirror the exam experience and help solidify your understanding of core project management concepts.By the end of this book, you will be able to develop creative solutions for complex issues faced in project management.
Ian Neil
CompTIA Security+ is a worldwide certification that establishes the fundamental knowledge required to perform core security functions and pursue an IT security career. CompTIA Security+ Certification Guide is a best-in-class exam study guide that covers all of CompTIA Security+ 501 exam objectives. It is authored by Ian Neil, who is a world-class trainer of CompTIA Security+ 501. Packed with self-assessment scenarios and realistic exam questions, this guide will help you master the core concepts to succeed in the exam the first time you take it. Using relevant examples, you will learn all the important security fundamentals from Certificates and Encryption to Identity and Access Management concepts. You will then dive into the important domains of the exam; namely, threats, attacks and vulnerabilities, technologies and tools, architecture and design, risk management, and cryptography and Public Key Infrastructure (PKI). This book comes with over 600 practice questions with detailed explanation that is at the exam level and also includes two mock exams to help you with your study plan. This guide will ensure that encryption and certificates are made easy for you.
Mark McGinley
Ace the globally recognized CompTIA Security+ SY0-701 certification exam by validating your expertise in essential cybersecurity concepts and practices through rigorously designed practice tests. Covering all the concepts tested in the CompTIA Security+ SY0-701 exam, this exam guide will help you evaluate your proficiency across five core security domains: general security concepts, threats and vulnerabilities with mitigations, security architecture, security operations, and program management.More than just another study guide, this book is a strategic preparation tool that focuses on assessing your retention of the material and evaluating your exam readiness rather than teaching theory. Packed with hundreds of expertly crafted questions, it mirrors the actual exam’s difficulty level and offers more than knowledge—you’ll develop the confidence and strategic thinking needed to excel on test day. To address the gaps in your knowledge, each question is paired with descriptive answers and in-depth explanations, transforming potential mistakes into powerful learning moments.By the end of this book, you’ll be primed to approach the CompTIA Security+ SY0-701 exam with the skills and expertise needed to succeed.
Mark McGinley
Ace the globally recognized CompTIA Security+ SY0-701 certification exam by validating your expertise in essential cybersecurity concepts and practices through rigorously designed practice tests. Covering all the concepts tested in the CompTIA Security+ SY0-701 exam, this exam guide will help you evaluate your proficiency across five core security domains: general security concepts, threats and vulnerabilities with mitigations, security architecture, security operations, and program management.More than just another study guide, this book is a strategic preparation tool that focuses on assessing your retention of the material and evaluating your exam readiness rather than teaching theory. Packed with hundreds of expertly crafted questions, it mirrors the actual exam’s difficulty level and offers more than knowledge—you’ll develop the confidence and strategic thinking needed to excel on test day. To address the gaps in your knowledge, each question is paired with descriptive answers and in-depth explanations, transforming potential mistakes into powerful learning moments.By the end of this book, you’ll be primed to approach the CompTIA Security+ SY0-701 exam with the skills and expertise needed to succeed.
Ian Neil
Looking to pass the CompTIA Network+ N10-009 exam and advance your IT career? Employers seek certified professionals who can design, secure, and troubleshoot modern networks. Memorizing concepts won’t cut it—you need a practical grasp of networking concepts, and this guide helps you build exactly that. Ian Neil, bestselling author of some of the most trusted CompTIA certification resources and a world-class CompTIA trainer, provides 100% coverage of all N10-009 exam objectives.You’ll start with the networking fundamentals, including the OSI model, topologies, ports, and protocols, then progress to configuring IPv4/IPv6 addressing, routing, switching, VLANs, and wireless networks. You’ll master transmission media and transceivers and strengthen your security expertise with VPNs, IPSec, NAC, IDS/IPS, Zero Trust, and firewalls.Beyond exam prep, this book explores cloud, virtualization, IoT, SDN, and SD-WAN, ensuring you’re prepared for modern IT environments. It helps build your troubleshooting skills using tools such as SNMP, NetFlow, Wireshark, log analysis, and traceroute.With practice questions across 25 chapters, 2 full-length online mock exams, 400 exam-style questions, and a 12% exam discount voucher, this guide equips you with the knowledge, experience, and confidence to earn your Network+ certification on the first try.
Ian Neil
Looking to pass the CompTIA Network+ N10-009 exam and advance your IT career? Employers seek certified professionals who can design, secure, and troubleshoot modern networks. Memorizing concepts won’t cut it—you need a practical grasp of networking concepts, and this guide helps you build exactly that. Ian Neil, bestselling author of some of the most trusted CompTIA certification resources and a world-class CompTIA trainer, provides 100% coverage of all N10-009 exam objectives.You’ll start with the networking fundamentals, including the OSI model, topologies, ports, and protocols, then progress to configuring IPv4/IPv6 addressing, routing, switching, VLANs, and wireless networks. You’ll master transmission media and transceivers and strengthen your security expertise with VPNs, IPSec, NAC, IDS/IPS, Zero Trust, and firewalls.Beyond exam prep, this book explores cloud, virtualization, IoT, SDN, and SD-WAN, ensuring you’re prepared for modern IT environments. It helps build your troubleshooting skills using tools such as SNMP, NetFlow, Wireshark, log analysis, and traceroute.With practice questions across 25 chapters, 2 full-length online mock exams, 400 exam-style questions, and a 12% exam discount voucher, this guide equips you with the knowledge, experience, and confidence to earn your Network+ certification on the first try.
Computational Physics. A Comprehensive Guide to Numerical Methods in Physics
Mercury Learning and Information, Darren Walker
This updated edition introduces computational physics for performing experiments on the computer. It provides a grounding in scientific programming with examples in the context of physics problems. Using C++ as the primary language, it covers interpolation, integration, and solving differential equations, from simple concepts to advanced topics. The book includes a chapter on high-performance computing and parallel programming.Understanding computational physics is crucial for data manipulation and real-world simulations. The book starts with introductory topics and progresses to advanced material, including a C++ library and sample programs. Readers will learn problem-solving methods and constructing models.This journey equips readers with skills for scientific tasks, demonstrating efficient problem-solving and model construction. The practical approach ensures users can apply these concepts in real-world scenarios, making it an essential resource for those interested in computational physics.
Lauren Mullennex, Nate Bachmeier, Jay Rao
Computer vision (CV) is a field of artificial intelligence that helps transform visual data into actionable insights to solve a wide range of business challenges. This book provides prescriptive guidance to anyone looking to learn how to approach CV problems for quickly building and deploying production-ready models.You’ll begin by exploring the applications of CV and the features of Amazon Rekognition and Amazon Lookout for Vision. The book will then walk you through real-world use cases such as identity verification, real-time video analysis, content moderation, and detecting manufacturing defects that’ll enable you to understand how to implement AWS AI/ML services. As you make progress, you'll also use Amazon SageMaker for data annotation, training, and deploying CV models. In the concluding chapters, you'll work with practical code examples, and discover best practices and design principles for scaling, reducing cost, improving the security posture, and mitigating bias of CV workloads.By the end of this AWS book, you'll be able to accelerate your business outcomes by building and implementing CV into your production environments with the help of AWS AI/ML services.
Matthew Rever
Python is the ideal programming language for rapidly prototyping and developing production-grade codes for image processing and Computer Vision with its robust syntax and wealth of powerful libraries. This book will help you design and develop production-grade Computer Vision projects tackling real-world problems.With the help of this book, you will learn how to set up Anaconda and Python for the major OSes with cutting-edge third-party libraries for Computer Vision. You'll learn state-of-the-art techniques for classifying images, finding and identifying human postures, and detecting faces within videos. You will use powerful machine learning tools such as OpenCV, Dlib, and TensorFlow to build exciting projects such as classifying handwritten digits, detecting facial features,and much more. The book also covers some advanced projects, such as reading text from license plates from real-world images using Google’s Tesseract software, and tracking human body poses using DeeperCut within TensorFlow.By the end of this book, you will have the expertise required to build your own Computer Vision projects using Python and its associated libraries.
Matthew Rever
Python is the ideal programming language for rapidly prototyping and developing production-grade codes for image processing and Computer Vision with its robust syntax and wealth of powerful libraries. This book will help you design and develop production-grade Computer Vision projects tackling real-world problems.With the help of this book, you will learn how to set up Anaconda and Python for the major OSes with cutting-edge third-party libraries for Computer Vision. You'll learn state-of-the-art techniques for classifying images, finding and identifying human postures, and detecting faces within videos. You will use powerful machine learning tools such as OpenCV, Dlib, and TensorFlow to build exciting projects such as classifying handwritten digits, detecting facial features,and much more. The book also covers some advanced projects, such as reading text from license plates from real-world images using Google’s Tesseract software, and tracking human body poses using DeeperCut within TensorFlow.By the end of this book, you will have the expertise required to build your own Computer Vision projects using Python and its associated libraries.
Amin Ahmadi Tazehkandi
Developers have been using OpenCV library to develop computer vision applications for a long time. However, they now need a more effective tool to get the job done and in a much better and modern way. Qt is one of the major frameworks available for this task at the moment. This book will teach you to develop applications with the combination of OpenCV 3 and Qt5, and how to create cross-platform computer vision applications. We’ll begin by introducing Qt, its IDE, and its SDK. Next you’ll learn how to use the OpenCV API to integrate both tools, and see how to configure Qt to use OpenCV. You’ll go on to build a full-fledged computer vision application throughout the book. Later, you’ll create a stunning UI application using the Qt widgets technology, where you’ll display the images after they are processed in an efficient way. At the end of the book, you’ll learn how to convert OpenCV Mat to Qt QImage. You’ll also see how to efficiently process images to filter them, transform them, detect or track objects as well as analyze video. You’ll become better at developing OpenCV applications.
Content marketing. Od strategii do efektów
Justyna Bakalarska-Stankiewicz
Złów złotą rybkę w oceanie internetu! Wiek XXI to epoka informacji. A może raczej: nadmiaru informacji. Internet w coraz mniejszym stopniu jest źródłem cennej wiedzy, przypomina raczej śmietnik przepełniony fake newsami i milionami bodźców oddziałujących na odbiorców w każdej sekundzie. Do tego stanu rzeczy przyczyniają się także marketerzy, którzy w obliczu ślepoty bannerowej czy też programów do blokowania reklam szukają coraz skuteczniejszych metod przykucia uwagi odbiorcy. Nie jest to łatwe. Według niektórych źródeł średni czas koncentracji internautów w ostatnich latach spadł do 8 sekund - to podobno tyle, ile trwa utrzymanie uwagi przez złotą rybkę. Dlatego sposobem na zwiększenie zainteresowania internetowych "złotych rybek" miał być content marketing, czyli marketing treści. Jednak ten modny trend, realizowany w niewłaściwy sposób, wcale nie prowadzi do osiągnięcia zadowalających efektów. Zamiast tego powoduje jeszcze większy chaos komunikacyjny. Jak temu zaradzić? Tu z pomocą przychodzi Justyna Bakalarska-Stankiewicz, autorka książki, z której dowiesz się między innymi: Czego content manager może się nauczyć z oper mydlanych? Dlaczego o swoim odbiorcy powinieneś myśleć jak o przyjacielu? Czy content marketing sprzedaje? Czemu panda, pingwin i koliber powinny mieć wpływ na Twoją strategię? Jak być SMART przy określaniu celów w marketingu treści? W czym marketer powinien upodobnić się do Jezusa? Czy Twoja firma to Mędrzec czy Błazen? Jak pisać do odbiorców, którzy nie czytają? A także wielu innych rzeczy, dzięki którym stworzysz naprawdę skuteczną strategię contentmarketingową dla swojej firmy i marki osobistej.
Paul Swartout
Over the past few years, Continuous Delivery (CD) and DevOps have been in the spotlight in tech media, at conferences, and in boardrooms alike. Many articles and books have been written covering the technical aspects of CD and DevOps, yet the vast majority of the industry doesn’t fully understand what they actually are and how, if adopted correctly they can help organizations drastically change the way they deliver value. This book will help you figure out how CD and DevOps can help you to optimize, streamline, and improve the way you work to consistently deliver quality software. In this edition, you’ll be introduced to modern tools, techniques, and examples to help you understand what the adoption of CD and DevOps entails. It provides clear and concise insights in to what CD and DevOps are all about, how to go about both preparing for and adopting them, and what quantifiable value they bring. You will be guided through the various stages of adoption, the impact they will have on your business and those working within it, how to overcome common problems, and what to do once CD and DevOps have become truly embedded. Included within this book are some real-world examples, tricks, and tips that will help ease the adoption process and allow you to fully utilize the power of CD and DevOps
Sander Rossel
The challenge faced by many teams while implementing Continuous Deployment is that it requires the use of many tools and processes that all work together. Learning and implementing all these tools (correctly) takes a lot of time and effort, leading people to wonder whether it's really worth it. This book sets up a project to show you the different steps, processes, and tools in Continuous Deployment and the actual problems they solve.We start by introducing Continuous Integration (CI), deployment, and delivery as well as providing an overview of the tools used in CI. You'll then create a web app and see how Git can be used in a CI environment. Moving on, you'll explore unit testing using Jasmine and browser testing using Karma and Selenium for your app. You'll also find out how to automate tasks using Gulp and Jenkins. Next, you'll get acquainted with database integration for different platforms, such as MongoDB and PostgreSQL. Finally, you'll set up different Jenkins jobs to integrate with Node.js and C# projects, and Jenkins pipelines to make branching easier.By the end of the book, you'll have implemented Continuous Delivery and deployment from scratch.
Xiaoquan Kong, Guan Wang, Alan Nichol
The Rasa framework enables developers to create industrial-strength chatbots using state-of-the-art natural language processing (NLP) and machine learning technologies quickly, all in open source.Conversational AI with Rasa starts by showing you how the two main components at the heart of Rasa work – Rasa NLU (natural language understanding) and Rasa Core. You'll then learn how to build, configure, train, and serve different types of chatbots from scratch by using the Rasa ecosystem. As you advance, you'll use form-based dialogue management, work with the response selector for chitchat and FAQ-like dialogs, make use of knowledge base actions to answer questions for dynamic queries, and much more. Furthermore, you'll understand how to customize the Rasa framework, use conversation-driven development patterns and tools to develop chatbots, explore what your bot can do, and easily fix any mistakes it makes by using interactive learning. Finally, you'll get to grips with deploying the Rasa system to a production environment with high performance and high scalability and cover best practices for building an efficient and robust chat system.By the end of this book, you'll be able to build and deploy your own chatbots using Rasa, addressing the common pain points encountered in the chatbot life cycle.
Leondra R. Gonzalez, Angela Baltes, Aaren Stubberfield
The data science job market is saturated with professionals of all backgrounds, including academics, researchers, bootcampers, and Massive Open Online Course (MOOC) graduates. This poses a challenge for companies seeking the best person to fill their roles. At the heart of this selection process is the data science interview, a crucial juncture that determines the best fit for both the candidate and the company.Cracking the Data Science Interview provides expert guidance on approaching the interview process with full preparation and confidence. Starting with an introduction to the modern data science landscape, you’ll find tips on job hunting, resume writing, and creating a top-notch portfolio. You’ll then advance to topics such as Python, SQL databases, Git, and productivity with shell scripting and Bash. Building on this foundation, you'll delve into the fundamentals of statistics, laying the groundwork for pre-modeling concepts, machine learning, deep learning, and generative AI. The book concludes by offering insights into how best to prepare for the intensive data science interview.By the end of this interview guide, you’ll have gained the confidence, business acumen, and technical skills required to distinguish yourself within this competitive landscape and land your next data science job.
Chandru Shankar, Vincent Bellefroid, Nilesh Thakkar
Robert S. Sutor
Dancing with Qubits, Second Edition, is a comprehensive quantum computing textbook that starts with an overview of why quantum computing is so different from classical computing and describes several industry use cases where it can have a major impact. A full description of classical computing and the mathematical underpinnings of quantum computing follows, helping you better understand concepts such as superposition, entanglement, and interference. Next up are circuits and algorithms, both basic and sophisticated, as well as a survey of the physics and engineering ideas behind how quantum computing hardware is built. Finally, the book looks to the future and gives you guidance on understanding how further developments may affect you.This new edition is updated throughout with more than 100 new exercises and includes new chapters on NISQ algorithms and quantum machine learning.Understanding quantum computing requires a lot of math, and this book doesn't shy away from the necessary math concepts you'll need. Each topic is explained thoroughly and with helpful examples, leaving you with a solid foundation of knowledge in quantum computing that will help you pursue and leverage quantum-led technologies.
Dancing with Qubits. How quantum computing works and how it can change the world
Robert S. Sutor
Quantum computing is making us change the way we think about computers. Quantum bits, a.k.a. qubits, can make it possible to solve problems that would otherwise be intractable with current computing technology. Dancing with Qubits is a quantum computing textbook that starts with an overview of why quantum computing is so different from classical computing and describes several industry use cases where it can have a major impact. From there it moves on to a fuller description of classical computing and the mathematical underpinnings necessary to understand such concepts as superposition, entanglement, and interference. Next up is circuits and algorithms, both basic and more sophisticated. It then nicely moves on to provide a survey of the physics and engineering ideas behind how quantum computing hardware is built. Finally, the book looks to the future and gives you guidance on understanding how further developments will affect you.Really understanding quantum computing requires a lot of math, and this book doesn't shy away from the necessary math concepts you'll need. Each topic is introduced and explained thoroughly, in clear English with helpful examples.
Dancing with Qubits. How quantum computing works and how it can change the world
Robert S. Sutor
Quantum computing is making us change the way we think about computers. Quantum bits, a.k.a. qubits, can make it possible to solve problems that would otherwise be intractable with current computing technology. Dancing with Qubits is a quantum computing textbook that starts with an overview of why quantum computing is so different from classical computing and describes several industry use cases where it can have a major impact. From there it moves on to a fuller description of classical computing and the mathematical underpinnings necessary to understand such concepts as superposition, entanglement, and interference. Next up is circuits and algorithms, both basic and more sophisticated. It then nicely moves on to provide a survey of the physics and engineering ideas behind how quantum computing hardware is built. Finally, the book looks to the future and gives you guidance on understanding how further developments will affect you.Really understanding quantum computing requires a lot of math, and this book doesn't shy away from the necessary math concepts you'll need. Each topic is introduced and explained thoroughly, in clear English with helpful examples.
Cuantum Technologies LLC
Embark on a comprehensive journey through data analysis with Python. Begin with an introduction to data analysis and Python, setting a strong foundation before delving into Python programming basics. Learn to set up your data analysis environment, ensuring you have the necessary tools and libraries at your fingertips. As you progress, gain proficiency in NumPy for numerical operations and Pandas for data manipulation, mastering the skills to handle and transform data efficiently.Proceed to data visualization with Matplotlib and Seaborn, where you'll create insightful visualizations to uncover patterns and trends. Understand the core principles of exploratory data analysis (EDA) and data preprocessing, preparing your data for robust analysis. Explore probability theory and hypothesis testing to make data-driven conclusions and get introduced to the fundamentals of machine learning. Delve into supervised and unsupervised learning techniques, laying the groundwork for predictive modeling.To solidify your knowledge, engage with two practical case studies: sales data analysis and social media sentiment analysis. These real-world applications will demonstrate best practices and provide valuable tips for your data analysis projects.
Data Analysis with IBM SPSS Statistics. Implementing data modeling, descriptive statistics and ANOVA
James C. Mott, Ken Stehlik-Barry, James Sugrue,...
SPSS Statistics is a software package used for logical batched and non-batched statistical analysis. Analytical tools such as SPSS can readily provide even a novice user with an overwhelming amount of information and a broad range of options for analyzing patterns in the data. The journey starts with installing and configuring SPSS Statistics for first use and exploring the data to understand its potential (as well as its limitations). Use the right statistical analysis technique such as regression, classification and more, and analyze your data in the best possible manner. Work with graphs and charts to visualize your findings. With this information in hand, the discovery of patterns within the data can be undertaken. Finally, the high level objective of developing predictive models that can be applied to other situations will be addressed. By the end of this book, you will have a firm understanding of the various statistical analysis techniques offered by SPSS Statistics, and be able to master its use for data analysis with ease.
Duc Haba
Data is paramount in AI projects, especially for deep learning and generative AI, as forecasting accuracy relies on input datasets being robust. Acquiring additional data through traditional methods can be challenging, expensive, and impractical, and data augmentation offers an economical option to extend the dataset.The book teaches you over 20 geometric, photometric, and random erasing augmentation methods using seven real-world datasets for image classification and segmentation. You’ll also review eight image augmentation open source libraries, write object-oriented programming (OOP) wrapper functions in Python Notebooks, view color image augmentation effects, analyze safe levels and biases, as well as explore fun facts and take on fun challenges. As you advance, you’ll discover over 20 character and word techniques for text augmentation using two real-world datasets and excerpts from four classic books. The chapter on advanced text augmentation uses machine learning to extend the text dataset, such as Transformer, Word2vec, BERT, GPT-2, and others. While chapters on audio and tabular data have real-world data, open source libraries, amazing custom plots, and Python Notebook, along with fun facts and challenges.By the end of this book, you will be proficient in image, text, audio, and tabular data augmentation techniques.
Data driven marketing. O logicznym podejściu do podejmowania decyzji
Adrian Andrzejczyk
Jak korzystać z pozyskanych danych przy tworzeniu kampanii marketingowej? Data driven marketing jest koncepcją odnoszącą się bezpośrednio do używania statystyk, faktów i obiektywnych informacji w marketingu. Te precyzyjne, ukierunkowane działania mają pomóc w podejmowaniu lepszych decyzji, optymalizacji procesów czy ― idąc tropem marketingu 5.0 ― zastosowaniu AI jako wsparcia, jak również naśladowaniu pracy samych marketingowców. W efekcie marketing staje się efektywniejszy, co bezpośrednio pozytywnie wpływa na wyniki przedsiębiorstwa. Sam termin data driven marketing jest bardzo obszerny, mieszczą się w nim wszystkie pojęcia wspólne dla marketingu i analityki danych. Autor książki stara się zgłębić najważniejsze z nich i pokazać: Jak skuteczny może być marketing bazujący na danych Na czym bazują techniki analizy danych Dlaczego w marketingu online warto sięgać po narzędzia oferowane przez Google Które z nich są szczególnie przydatne w marketingowej analizie danych Jakimi rozwiązaniami można ewentualnie zastąpić narzędzia Google Książka w mediach: BiznesTuba.pl Przeczytam 52 Książki Bookstagram Detalistka.pl - Recenzja Books4Business Bookstagram
Vijaya Kumar Suda
Data labeling is the invisible hand that guides the power of artificial intelligence and machine learning. In today’s data-driven world, mastering data labeling is not just an advantage, it’s a necessity. Data Labeling in Machine Learning with Python empowers you to unearth value from raw data, create intelligent systems, and influence the course of technological evolution.With this book, you'll discover the art of employing summary statistics, weak supervision, programmatic rules, and heuristics to assign labels to unlabeled training data programmatically. As you progress, you'll be able to enhance your datasets by mastering the intricacies of semi-supervised learning and data augmentation. Venturing further into the data landscape, you'll immerse yourself in the annotation of image, video, and audio data, harnessing the power of Python libraries such as seaborn, matplotlib, cv2, librosa, openai, and langchain. With hands-on guidance and practical examples, you'll gain proficiency in annotating diverse data types effectively.By the end of this book, you’ll have the practical expertise to programmatically label diverse data types and enhance datasets, unlocking the full potential of your data.
Data Lake for Enterprises. Lambda Architecture for building enterprise data systems
Vivek Mishra, Tomcy John, Pankaj Misra
The term Data Lake has recently emerged as a prominent term in the big data industry. Data scientists can make use of it in deriving meaningful insights that can be used by businesses to redefine or transform the way they operate. Lambda architecture is also emerging as one of the very eminent patterns in the big data landscape, as it not only helps to derive useful information from historical data but also correlates real-time data to enable business to take critical decisions. This book tries to bring these two important aspects — data lake and lambda architecture—together.This book is divided into three main sections. The first introduces you to the concept of data lakes, the importance of data lakes in enterprises, and getting you up-to-speed with the Lambda architecture. The second section delves into the principal components of building a data lake using the Lambda architecture. It introduces you to popular big data technologies such as Apache Hadoop, Spark, Sqoop, Flume, and ElasticSearch. The third section is a highly practical demonstration of putting it all together, and shows you how an enterprise data lake can be implemented, along with several real-world use-cases. It also shows you how other peripheral components can be added to the lake to make it more efficient.By the end of this book, you will be able to choose the right big data technologies using the lambda architectural patterns to build your enterprise data lake.
Data Lakehouse in Action. Architecting a modern and scalable data analytics platform
Pradeep Menon
The Data Lakehouse architecture is a new paradigm that enables large-scale analytics. This book will guide you in developing data architecture in the right way to ensure your organization's success.The first part of the book discusses the different data architectural patterns used in the past and the need for a new architectural paradigm, as well as the drivers that have caused this change. It covers the principles that govern the target architecture, the components that form the Data Lakehouse architecture, and the rationale and need for those components. The second part deep dives into the different layers of Data Lakehouse. It covers various scenarios and components for data ingestion, storage, data processing, data serving, analytics, governance, and data security. The book's third part focuses on the practical implementation of the Data Lakehouse architecture in a cloud computing platform. It focuses on various ways to combine the Data Lakehouse pattern to realize macro-patterns, such as Data Mesh and Data Hub-Spoke, based on the organization's needs and maturity level. The frameworks introduced will be practical and organizations can readily benefit from their application.By the end of this book, you'll clearly understand how to implement the Data Lakehouse architecture pattern in a scalable, agile, and cost-effective manner.
Data Mining. Eksploracja danych w sieciach społecznościowych. Wydanie III
Matthew A. Russell, Mikhail Klassen
Internetu nie można rozważać wyłącznie jako tworu techniki. Powstanie tej sieci doprowadziło do rozwoju różnych zjawisk społecznych. Z tej perspektywy na szczególną uwagę zasługują media społecznościowe. Są źródłem informacji, które, właściwie spożytkowane, mogą przynieść niezły dochód. Mogą też dać odpowiedzi na wiele pytań zadawanych przez naukowców z różnych branż. Sama eksploracja tych danych przynosi sporo satysfakcji i radości. Zaskakujące przy tym jest to, że przygotowanie zestawu potrzebnych narzędzi i nauka posługiwania się nimi zabiera naprawdę niewiele czasu i nie wymaga specjalnych talentów! To trzecie, zaktualizowane wydanie popularnego podręcznika dla osób, które chcą zająć się wydobywaniem danych z sieci społecznościowych. Uwzględniono tu zmiany interfejsów API wprowadzone do poszczególnych platform i dodano rozdział o eksploracji Instagrama. Dowiesz się, jak dzięki danym z mediów społecznościowych określić sieć powiązań użytkowników, zorientować się, kto o czym mówi i gdzie się znajduje. Treść bogato zilustrowano przykładami kodu w Pythonie, a także plikami Jupyter Notebook lub kontenerów Dockera. Ciekawym elementem książki jest zbiór receptur dotyczących rozwiązywania konkretnych problemów z Twitterem. W tej książce między innymi: wprowadzenie do świata mediów społecznościowych przybliżenie bogactwa danych zawartych w mediach społecznościowych eksploracja danych za pomocą narzędzi Pythona 3 zaawansowane techniki eksploracji danych, w tym współczynniki TFIDF, podobieństwo kosinusów i rozpoznawanie obrazów tworzenie wizualizacji pozyskanych danych Jakie informacje dziś znajdziesz dzięki danym z Facebooka?