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Practical Cloud Security: A Guide for Secure Design and Deployment
by Chris DotsonWith rapidly changing architecture and API-driven automation, cloud platforms come with unique security challenges and opportunities. In this updated second edition, you'll examine security best practices for multivendor cloud environments, whether your company plans to move legacy on-premises projects to the cloud or build a new infrastructure from the ground up. Developers, IT architects, and security professionals will learn cloud-specific techniques for securing popular cloud platforms such as Amazon Web Services, Microsoft Azure, and IBM Cloud. IBM Distinguished Engineer Chris Dotson shows you how to establish data asset management, identity and access management (IAM), vulnerability management, network security, and incident response in your cloud environment. Learn the latest threats and challenges in the cloud security spaceManage cloud providers that store or process data or deliver administrative controlLearn how standard principles and concepts—such as least privilege and defense in depth—apply in the cloudUnderstand the critical role played by IAM in the cloudUse best tactics for detecting, responding, and recovering from the most common security incidentsManage various types of vulnerabilities, especially those common in multicloud or hybrid cloud architecturesExamine privileged access management in cloud environments
Practical Cloud-Native Java Development with MicroProfile: Develop and deploy scalable, resilient, and reactive cloud-native applications using MicroProfile 4.1
by David Chan Eric Herness Emily Jiang Andrew McCright John Alcorn Alasdair NottinghamWritten by leading MicroProfile experts, this book provides you with best practices for building enterprise-grade cloud-native applications using MicroProfile 4.1 and running them on Open Liberty with Docker, Kubernetes, and IstioKey FeaturesApply your knowledge of MicroProfile APIs to develop cloud-native applicationsUse MicroProfile Health to provide the startup, liveness, and readiness status of your enterprise applicationBuild an end-to-end stock trader project and containerize it to deploy to the cloud with Istio interactionBook DescriptionIn this cloud-native era, most applications are deployed in a cloud environment that is public, private, or a combination of both. To ensure that your application performs well in the cloud, you need to build an application that is cloud native. MicroProfile is one of the most popular frameworks for building cloud-native applications, and fits well with Kubernetes. As an open standard technology, MicroProfile helps improve application portability across all of MicroProfile's implementations.Practical Cloud-Native Java Development with MicroProfile is a comprehensive guide that helps you explore the advanced features and use cases of a variety of Jakarta and MicroProfile specifications. You'll start by learning how to develop a real-world stock trader application, and then move on to enhancing the application and adding day-2 operation considerations. You'll gradually advance to packaging and deploying the application. The book demonstrates the complete process of development through to deployment and concludes by showing you how to monitor the application's performance in the cloud.By the end of this book, you will master MicroProfile's latest features and be able to build fast and efficient cloud-native applications.What you will learnUnderstand best practices for applying the 12-Factor methodology while building cloud-native applicationsCreate client-server architecture using MicroProfile Rest Client and JAX-RSConfigure your cloud-native application using MicroProfile ConfigSecure your cloud-native application with MicroProfile JWTBecome well-versed with running your cloud-native applications in Open LibertyGrasp MicroProfile Open Tracing and learn how to use Jaeger to view trace spansDeploy Docker containers to Kubernetes and understand how to use ConfigMap and Secrets from KubernetesWho this book is forThis book is for Java application developers and architects looking to build efficient applications using an open standard framework that performs well in the cloud. DevOps engineers who want to understand how cloud-native applications work will also find this book useful. A basic understanding of Java, Docker, Kubernetes, and cloud is needed to get the most out of this book.
Practical CockroachDB: Building Fault-Tolerant Distributed SQL Databases
by Rob ReidGet a practical introduction to CockroachDB. This book starts with installation and foundational concepts and takes you through to creating clusters that are ready for production environments. You will learn how to create, optimize, and operate CockroarchDB clusters in single and multi-region environments. You will encounter anti-patterns to avoid, as well as testing techniques for integration and load testing. The book explains why CockroachDB exists, goes over its major benefits, and quickly transitions into installing and configuring CockroachDB. Just as quickly, you’ll be creating databases, getting data into those databases, and querying that data from your applications. You’ll progress to data privacy laws such as GDPR and CCPA, and learn how CockroachDB’s global distribution features can help you comply with ever-shifting data sovereignty regulations. From there, you’ll move into deployment topologies, guidance on integration testing and load testing, best practices, and a readiness checklist for production deployments. What You Will LearnDeploy and interact with CockroachDBDesign and optimize databases and tablesChoose the correct data types for modeling your dataProtect data with database and table encryptionAchieve compliance with international data privacy regulationsScale your databases in a way that enhances their performanceMonitor changes to the data and health of your databasesWho This Book Is ForDevelopers and database administrators who want to provide a secure, reliable, and effortlessly distributed home for their data; those who wish to use a modern tool to tackle the kinds of scaling challenges that have previously required dedicated teams of people to solve; anyone who wants to leverage their database to solve non-trivial, real-world challenges while protecting their data and users
Practical Computer Analysis of Switch Mode Power Supplies
by Johnny C. BennettWhen designing switch-mode power supplies (SMPSs), engineers need much more than simple "recipes" for analysis. Such plug-and-go instructions are not at all helpful for simulating larger and more complex circuits and systems. Offering more than merely a "cookbook," Practical Computer Analysis of Switch Mode Power Supplies provides a thorough understanding of the essential requirements for analyzing SMPS performance characteristics. It demonstrates the power of the circuit averaging technique when used with powerful computer circuit simulation programs. The book begins with SMPS fundamentals and the basics of circuit averaging models, reviewing most basic topologies and explaining all of their various modes of operation and control. The author then discusses the general analysis requirements of power supplies and how to develop the general types of SMPS models, demonstrating the use of SPICE for analysis. He examines the basic first-order analyses generally associated with SMPS performance along with more practical and detailed methods for developing SMPS and component models. The final chapter features the circuit-averaging macromodel of the integrated circuit PWM controller illustrated through analyses of three power supplies. Practical Computer Analysis of Switch Mode Power Supplies builds a strong foundation on the principles of SMPS analysis, enabling further development and advancement of the techniques while supplying meaningful insight into the process.
Practical Computer Vision Applications Using Deep Learning with CNNs: With Detailed Examples in Python Using TensorFlow and Kivy
by Ahmed Fawzy GadDeploy deep learning applications into production across multiple platforms. You will work on computer vision applications that use the convolutional neural network (CNN) deep learning model and Python. This book starts by explaining the traditional machine-learning pipeline, where you will analyze an image dataset. Along the way you will cover artificial neural networks (ANNs), building one from scratch in Python, before optimizing it using genetic algorithms. For automating the process, the book highlights the limitations of traditional hand-crafted features for computer vision and why the CNN deep-learning model is the state-of-art solution. CNNs are discussed from scratch to demonstrate how they are different and more efficient than the fully connected ANN (FCNN). You will implement a CNN in Python to give you a full understanding of the model.After consolidating the basics, you will use TensorFlow to build a practical image-recognition model that you will deploy to a web server using Flask, making it accessible over the Internet. Using Kivy and NumPy, you will create cross-platform data science applications with low overheads.This book will help you apply deep learning and computer vision concepts from scratch, step-by-step from conception to production. What You Will Learn Understand how ANNs and CNNs work Create computer vision applications and CNNs from scratch using PythonFollow a deep learning project from conception to production using TensorFlowUse NumPy with Kivy to build cross-platform data science applicationsWho This Book Is ForData scientists, machine learning and deep learning engineers, software developers.
Practical Computer Vision with SimpleCV: The Simple Way to Make Technology See
by Kurt Demaagd Anthony Oliver Nathan Oostendorp Katherine ScottLearn how to build your own computer vision (CV) applications quickly and easily with SimpleCV, an open source framework written in Python. Through examples of real-world applications, this hands-on guide introduces you to basic CV techniques for collecting, processing, and analyzing streaming digital images. You’ll then learn how to apply these methods with SimpleCV, using sample Python code. All you need to get started is a Windows, Mac, or Linux system, and a willingness to put CV to work in a variety of ways. Programming experience is optional.Capture images from several sources, including webcams, smartphones, and KinectFilter image input so your application processes only necessary informationManipulate images by performing basic arithmetic on pixel valuesUse feature detection techniques to focus on interesting parts of an imageWork with several features in a single image, using the NumPy and SciPy Python librariesLearn about optical flow to identify objects that change between two image framesUse SimpleCV’s command line and code editor to run examples and test techniques
Practical Computer Vision: Extract Insightful Information From Images Using Tensorflow, Keras, And Opencv
by Abhinav DadhichComputer Vision is a broadly used term associated with acquiring, processing, and analyzing images. This book will show you how you can perform various Computer Vision techniques in the most practical way possible. Right from capturing images from various sources, you will learn how to perform image filtering/manipulation and detect features in your images. As you go through the chapters, you'll work with increasingly complex algorithms to develop complex Computer Vision applications
Practical Computer Vision: Extract insightful information from images using TensorFlow, Keras, and OpenCV
by Abhinav DadhichA practical guide designed to get you from basics to current state of art in computer vision systems. Key Features Master the different tasks associated with Computer Vision and develop your own Computer Vision applications with ease Leverage the power of Python, Tensorflow, Keras, and OpenCV to perform image processing, object detection, feature detection and more With real-world datasets and fully functional code, this book is your one-stop guide to understanding Computer Vision Book Description In this book, you will find several recently proposed methods in various domains of computer vision. You will start by setting up the proper Python environment to work on practical applications. This includes setting up libraries such as OpenCV, TensorFlow, and Keras using Anaconda. Using these libraries, you'll start to understand the concepts of image transformation and filtering. You will find a detailed explanation of feature detectors such as FAST and ORB; you'll use them to find similar-looking objects. With an introduction to convolutional neural nets, you will learn how to build a deep neural net using Keras and how to use it to classify the Fashion-MNIST dataset. With regard to object detection, you will learn the implementation of a simple face detector as well as the workings of complex deep-learning-based object detectors such as Faster R-CNN and SSD using TensorFlow. You'll get started with semantic segmentation using FCN models and track objects with Deep SORT. Not only this, you will also use Visual SLAM techniques such as ORB-SLAM on a standard dataset. By the end of this book, you will have a firm understanding of the different computer vision techniques and how to apply them in your applications. What you will learn Learn the basics of image manipulation with OpenCV Implement and visualize image filters such as smoothing, dilation, histogram equalization, and more Set up various libraries and platforms, such as OpenCV, Keras, and Tensorflow, in order to start using computer vision, along with appropriate datasets for each chapter, such as MSCOCO, MOT, and Fashion-MNIST Understand image transformation and downsampling with practical implementations. Explore neural networks for computer vision and convolutional neural networks using Keras Understand working on deep-learning-based object detection such as Faster- R-CNN, SSD, and more Explore deep-learning-based object tracking in action Understand Visual SLAM techniques such as ORB-SLAMWho this book is for This book is for machine learning practitioners and deep learning enthusiasts who want to understand and implement various tasks associated with Computer Vision and image processing in the most practical manner possible. Some programming experience would be beneficial while knowing Python would be an added bonus.
Practical Concurrent Haskell
by Stefania Loredana Nita Marius MihailescuLearn to use the APIs and frameworks for parallel and concurrent applications in Haskell. This book will show you how to exploit multicore processors with the help of parallelism in order to increase the performance of your applications. Practical Concurrent Haskell teaches you how concurrency enables you to write programs using threads for multiple interactions. After accomplishing this, you will be ready to make your move into application development and portability with applications in cloud computing and big data. You'll use MapReduce and other, similar big data tools as part of your Haskell big data applications development. What You'll Learn Program with Haskell Harness concurrency to Haskell Apply Haskell to big data and cloud computing applications Use Haskell concurrency design patterns in big data Accomplish iterative data processing on big data using Haskell Use MapReduce and work with Haskell on large clusters Who This Book Is For Those with at least some prior experience with Haskell and some prior experience with big data in another programming language such as Java, C#, Python, or C++.
Practical Contiki-NG: Programming for Wireless Sensor Networks
by Agus KurniawanExplore how to develop and implement wireless server networks (WSN) using Contiki-NG, branded as the operating system for the IoT. The book explains Contiki-NG’s advantages in sensing, communication, and energy optimization and enables you to begin solving problems in automation with WSN.Practical Contiki-NG is a guide to getting started with Contiki-NG programming featuring projects that demonstrate a variety of applications. This book takes a practical and content-driven approach to the latest technologies, including Raspberry Pi, IoT and cloud servers. Readers will go through step-by-step guides and sample scenarios such as sensing, actuating, connectivity, building middleware, and utilizing IoT and cloud-based technologies.If you're looking to go from zero to hero in using Contiki-NG to build Wireless Sensor Network (WSN) applications then this is the book for you. What You’ll LearnPrepare and set up Contiki-NG developmentReview the basics of the Contiki-NG platform to build Wireless Sensor Networks (WSN)Develop your own Contiki-NG programPerform sensing and actuating on the Contiki-NG platformImplement a middleware for Contiki-NG motesBuild a simple IoT program using the Contiki-NG environmentWho This Book Is ForDevelopers, students, researchers and anyone who has an interest in Wireless Sensor Network (WSN).
Practical Convolutional Neural Networks: Implement advanced deep learning models using Python
by Md. Rezaul Karim Mohit Sewak Pradeep PujariOne stop guide to implementing award-winning, and cutting-edge CNN architectures Key Features Fast-paced guide with use cases and real-world examples to get well versed with CNN techniques Implement CNN models on image classification, transfer learning, Object Detection, Instance Segmentation, GANs and more Implement powerful use-cases like image captioning, reinforcement learning for hard attention, and recurrent attention models Book Description Convolutional Neural Network (CNN) is revolutionizing several application domains such as visual recognition systems, self-driving cars, medical discoveries, innovative eCommerce and more.You will learn to create innovative solutions around image and video analytics to solve complex machine learning and computer vision related problems and implement real-life CNN models. This book starts with an overview of deep neural networkswith the example of image classification and walks you through building your first CNN for human face detector. We will learn to use concepts like transfer learning with CNN, and Auto-Encoders to build very powerful models, even when not much of supervised training data of labeled images is available. Later we build upon the learning achieved to build advanced vision related algorithms for object detection, instance segmentation, generative adversarial networks, image captioning, attention mechanisms for vision, and recurrent models for vision. By the end of this book, you should be ready to implement advanced, effective and efficient CNN models at your professional project or personal initiatives by working on complex image and video datasets. What you will learn -From CNN basic building blocks to advanced concepts understand practical areas they can be applied to -Build an image classifier CNN model to understand how different components interact with each other, and then learn how to optimize it -Learn different algorithms that can be applied to Object Detection, and Instance Segmentation - Learn advanced concepts like attention mechanisms for CNN to improve prediction accuracy -Understand transfer learning and implement award-winning CNN architectures like AlexNet, VGG, GoogLeNet, ResNet and more -Understand the working of generative adversarial networks and how it can create new, unseen images Who this book is for This book is for data scientists, machine learning and deep learning practitioners, Cognitive and Artificial Intelligence enthusiasts who want to move one step further in building Convolutional Neural Networks. Get hands-on experience with extreme datasets and different CNN architectures to build efficient and smart ConvNet models. Basic knowledge of deep learning concepts and Python programming language is expected.
Practical Core Software Security: A Reference Framework
by Anmol Misra Mark S. Merkow James F. RansomeAs long as humans write software, the key to successful software security is making the software development program process more efficient and effective. Although the approach of this textbook includes people, process, and technology approaches to software security, Practical Core Software Security: A Reference Framework stresses the people element of software security, which is still the most important part to manage as software is developed, controlled, and exploited by humans. The text outlines a step-by-step process for software security that is relevant to today’s technical, operational, business, and development environments. It focuses on what humans can do to control and manage a secure software development process using best practices and metrics. Although security issues will always exist, students learn how to maximize an organization’s ability to minimize vulnerabilities in software products before they are released or deployed by building security into the development process. The authors have worked with Fortune 500 companies and have often seen examples of the breakdown of security development lifecycle (SDL) practices. The text takes an experience-based approach to apply components of the best available SDL models in dealing with the problems described above. Software security best practices, an SDL model, and framework are presented in this book. Starting with an overview of the SDL, the text outlines a model for mapping SDL best practices to the software development life cycle (SDLC). It explains how to use this model to build and manage a mature SDL program. Exercises and an in-depth case study aid students in mastering the SDL model. Professionals skilled in secure software development and related tasks are in tremendous demand today. The industry continues to experience exponential demand that should continue to grow for the foreseeable future. This book can benefit professionals as much as students. As they integrate the book’s ideas into their software security practices, their value increases to their organizations, management teams, community, and industry. About the Authors Dr. James Ransome, PhD, CISSP, CISM is a veteran of numerous chief information security officer (CISO), chief security officer (CSO), and chief production security officer (CPSO) roles, as well as an author and co-author of numerous cybersecurity books. Anmol Misra is an accomplished leader, researcher, author, and security expert with over 16 years of experience in technology and cybersecurity. Mark S. Merkow, CISSP, CISM, CSSLP has over 25 years of experience in corporate information security and 17 years in the AppSec space helping to establish and lead application security initiatives to success and sustainment.
Practical Criminal Investigations in Correctional Facilities (ISSN)
by William R. BellAN INSIDE LOOK INTO INVESTIGATING THE MOST VIOLENT SUB-CULTURE IN THE WORLDOnce an offender is behind bars, many people believe that he is no longer a threat to society. However, the felonious activities of confined inmates reach out into society every day. These inmates run lucrative drug operations, commit fraud, hire contract murders, an
Practical Cryptography in Python: Learning Correct Cryptography by Example
by Seth James Nielson Christopher K. MonsonDevelop a greater intuition for the proper use of cryptography. This book teaches the basics of writing cryptographic algorithms in Python, demystifies cryptographic internals, and demonstrates common ways cryptography is used incorrectly. Cryptography is the lifeblood of the digital world’s security infrastructure. From governments around the world to the average consumer, most communications are protected in some form or another by cryptography. These days, even Google searches are encrypted. Despite its ubiquity, cryptography is easy to misconfigure, misuse, and misunderstand.Developers building cryptographic operations into their applications are not typically experts in the subject, and may not fully grasp the implication of different algorithms, modes, and other parameters. The concepts in this book are largely taught by example, including incorrect uses of cryptography and how "bad" cryptography can be broken. By digging into the guts of cryptography, you can experience what works, what doesn't, and why. What You’ll LearnUnderstand where cryptography is used, why, and how it gets misusedKnow what secure hashing is used for and its basic propertiesGet up to speed on algorithms and modes for block ciphers such as AES, and see how bad configurations breakUse message integrity and/or digital signatures to protect messagesUtilize modern symmetric ciphers such as AES-GCM and CHACHAPractice the basics of public key cryptography, including ECDSA signaturesDiscover how RSA encryption can be broken if insecure padding is usedEmploy TLS connections for secure communicationsFind out how certificates work and modern improvements such as certificate pinning and certificate transparency (CT) logs Who This Book Is For IT administrators and software developers familiar with Python. Although readers may have some knowledge of cryptography, the book assumes that the reader is starting from scratch.
Practical Cryptography: Algorithms and Implementations Using C++
by Saiful Azad Al-Sakib Khan PathanCryptography, the science of encoding and decoding information, allows people to do online banking, online trading, and make online purchases, without worrying that their personal information is being compromised. The dramatic increase of information transmitted electronically has led to an increased reliance on cryptography. This book discusses th
Practical Cyber Forensics: An Incident-Based Approach to Forensic Investigations
by Niranjan ReddyBecome an effective cyber forensics investigator and gain a collection of practical, efficient techniques to get the job done. Diving straight into a discussion of anti-forensic techniques, this book shows you the many ways to effectively detect them. Now that you know what you are looking for, you’ll shift your focus to network forensics, where you cover the various tools available to make your network forensics process less complicated. Following this, you will work with cloud and mobile forensic techniques by considering the concept of forensics as a service (FaSS), giving you cutting-edge skills that will future-proof your career.Building on this, you will learn the process of breaking down malware attacks, web attacks, and email scams with case studies to give you a clearer view of the techniques to be followed. Another tricky technique is SSD forensics, so the author covers this in detail to give you the alternative analysis techniques you’ll need. To keep you up to speed on contemporary forensics, Practical Cyber Forensics includes a chapter on Bitcoin forensics, where key crypto-currency forensic techniques will be shared. Finally, you will see how to prepare accurate investigative reports. What You Will LearnCarry out forensic investigation on Windows, Linux, and macOS systemsDetect and counter anti-forensic techniques Deploy network, cloud, and mobile forensicsInvestigate web and malware attacksWrite efficient investigative reportsWho This Book Is ForIntermediate infosec professionals looking for a practical approach to investigative cyber forensics techniques.
Practical Cyber Intelligence: A Hands-on Guide to Digital Forensics
by Adam Tilmar JakobsenOverview of the latest techniques and practices used in digital forensics and how to apply them to the investigative process Practical Cyber Intelligence provides a thorough and practical introduction to the different tactics, techniques, and procedures that exist in the field of cyber investigation and cyber forensics to collect, preserve, and analyze digital evidence, enabling readers to understand the digital landscape and analyze legacy devices, current models, and models that may be created in the future. Readers will learn how to determine what evidence exists and how to find it on a device, as well as what story it tells about the activities on the device. Over 100 images and tables are included to aid in reader comprehension, and case studies are included at the end of the book to elucidate core concepts throughout the text. To get the most value from this book, readers should be familiar with how a computer operates (e.g., CPU, RAM, and disk), be comfortable interacting with both Windows and Linux operating systems as well as Bash and PowerShell commands and have a basic understanding of Python and how to execute Python scripts. Practical Cyber Intelligence includes detailed information on: OSINT, the method of using a device’s information to find clues and link a digital avatar to a person, with information on search engines, profiling, and infrastructure mappingWindow forensics, covering the Windows registry, shell items, the event log and much more Mobile forensics, understanding the difference between Android and iOS and where key evidence can be found on the device Focusing on methodology that is accessible to everyone without any special tools, Practical Cyber Intelligence is an essential introduction to the topic for all professionals looking to enter or advance in the field of cyber investigation, including cyber security practitioners and analysts and law enforcement agents who handle digital evidence.
Practical Cyber Intelligence: How action-based intelligence can be an effective response to incidents
by Wilson BautistaYour one stop solution to implement a Cyber Defense Intelligence program in to your organisation.Key FeaturesIntelligence processes and procedures for response mechanismsMaster F3EAD to drive processes based on intelligenceThreat modeling and intelligent frameworksCase studies and how to go about building intelligent teamsBook DescriptionCyber intelligence is the missing link between your cyber defense operation teams, threat intelligence, and IT operations to provide your organization with a full spectrum of defensive capabilities. This book kicks off with the need for cyber intelligence and why it is required in terms of a defensive framework.Moving forward, the book provides a practical explanation of the F3EAD protocol with the help of examples. Furthermore, we learn how to go about threat models and intelligence products/frameworks and apply them to real-life scenarios. Based on the discussion with the prospective author I would also love to explore the induction of a tool to enhance the marketing feature and functionality of the book.By the end of this book, you will be able to boot up an intelligence program in your organization based on the operation and tactical/strategic spheres of Cyber defense intelligence.What you will learn Learn about the Observe-Orient-Decide-Act (OODA) loop and it's applicability to security Understand tactical view of Active defense concepts and their application in today's threat landscape Get acquainted with an operational view of the F3EAD process to drive decision making within an organization Create a Framework and Capability Maturity Model that integrates inputs and outputs from key functions in an information security organization Understand the idea of communicating with the Potential for Exploitability based on cyber intelligenceWho this book is forThis book targets incident managers, malware analysts, reverse engineers, digital forensics specialists, and intelligence analysts; experience in, or knowledge of, security operations, incident responses or investigations is desirable so you can make the most of the subjects presented.
Practical Cybersecurity Architecture: A guide to creating and implementing robust designs for cybersecurity architects
by Ed Moyle Diana KelleyPlan and design robust security architectures to secure your organization's technology landscape and the applications you developKey FeaturesLeverage practical use cases to successfully architect complex security structuresLearn risk assessment methodologies for the cloud, networks, and connected devicesUnderstand cybersecurity architecture to implement effective solutions in medium-to-large enterprisesBook DescriptionCybersecurity architects work with others to develop a comprehensive understanding of the business' requirements. They work with stakeholders to plan designs that are implementable, goal-based, and in keeping with the governance strategy of the organization.With this book, you'll explore the fundamentals of cybersecurity architecture: addressing and mitigating risks, designing secure solutions, and communicating with others about security designs. The book outlines strategies that will help you work with execution teams to make your vision a concrete reality, along with covering ways to keep designs relevant over time through ongoing monitoring, maintenance, and continuous improvement. As you progress, you'll also learn about recognized frameworks for building robust designs as well as strategies that you can adopt to create your own designs.By the end of this book, you will have the skills you need to be able to architect solutions with robust security components for your organization, whether they are infrastructure solutions, application solutions, or others.What you will learnExplore ways to create your own architectures and analyze those from othersUnderstand strategies for creating architectures for environments and applicationsDiscover approaches to documentation using repeatable approaches and toolsDelve into communication techniques for designs, goals, and requirementsFocus on implementation strategies for designs that help reduce riskBecome well-versed with methods to apply architectural discipline to your organizationWho this book is forIf you are involved in the process of implementing, planning, operating, or maintaining cybersecurity in an organization, then this security book is for you. This includes security practitioners, technology governance practitioners, systems auditors, and software developers invested in keeping their organizations secure. If you're new to cybersecurity architecture, the book takes you through the process step by step; for those who already work in the field and have some experience, the book presents strategies and techniques that will help them develop their skills further.
Practical D3.js
by Tarek Amr Rayna StamboliyskaPractical D3. js is your indispensable guide to mastering the efficient use of this exciting JavaScript data visualization library. You will learn what data visualization is, how to work with it, and how to think like a D3. js expert, both practically and theoretically. This book does not just show you how to use D3. js, it teaches you how to think like a data scientist and work with the data in the real world. You will learn how to get the data, how to clean and refine it, and how to display it in the best charts and layouts. Uniquely, this book intertwines the technical details of D3. js with practical topics such as data journalism and the use of open government data. Written by leading data scientists Tarek Amr and Rayna Stamboliyska, Practical D3. js is your indispensable guide to using D3. js in the real world - add it to your library today. What you'll learn How to think like a data scientist and present data in the best way What structure and design strategies you can use for compelling data visualization How to use data binding, animations and events, scales, and color pickers How to use shapes, path generators, arcs and polygons Who this book is for This book is for anyone who wants to learn to master the use of D3. js in a practical manner, while still learning the important theoretical aspects needed to enable them to work with their data in the best possible way.
Practical Data Analysis
by Hector CuestaEach chapter of the book quickly introduces a key 'theme' of Data Analysis, before immersing you in the practical aspects of each theme. You'll learn quickly how to perform all aspects of Data Analysis.Practical Data Analysis is a book ideal for home and small business users who want to slice & dice the data they have on hand with minimum hassle.
Practical Data Analysis - Second Edition
by Hector Cuesta Dr Sampath KumarA practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache Spark About This Book * Learn to use various data analysis tools and algorithms to classify, cluster, visualize, simulate, and forecast your data * Apply Machine Learning algorithms to different kinds of data such as social networks, time series, and images * A hands-on guide to understanding the nature of data and how to turn it into insight Who This Book Is For This book is for developers who want to implement data analysis and data-driven algorithms in a practical way. It is also suitable for those without a background in data analysis or data processing. Basic knowledge of Python programming, statistics, and linear algebra is assumed. What You Will Learn * Acquire, format, and visualize your data * Build an image-similarity search engine * Generate meaningful visualizations anyone can understand * Get started with analyzing social network graphs * Find out how to implement sentiment text analysis * Install data analysis tools such as Pandas, MongoDB, and Apache Spark * Get to grips with Apache Spark * Implement machine learning algorithms such as classification or forecasting In Detail Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you'll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark. Style and approach This is a hands-on guide to data analysis and data processing. The concrete examples are explained with simple code and accessible data.
Practical Data Analysis Cookbook
by Tomasz DrabasOver 60 practical recipes on data exploration and analysis About This Book * Clean dirty data, extract accurate information, and explore the relationships between variables * Forecast the output of an electric plant and the water flow of American rivers using pandas, NumPy, Statsmodels, and scikit-learn * Find and extract the most important features from your dataset using the most efficient Python libraries Who This Book Is For If you are a beginner or intermediate-level professional who is looking to solve your day-to-day, analytical problems with Python, this book is for you. Even with no prior programming and data analytics experience, you will be able to finish each recipe and learn while doing so. What You Will Learn * Read, clean, transform, and store your data usng Pandas and OpenRefine * Understand your data and explore the relationships between variables using Pandas and D3.js * Explore a variety of techniques to classify and cluster outbound marketing campaign calls data of a bank using Pandas, mlpy, NumPy, and Statsmodels * Reduce the dimensionality of your dataset and extract the most important features with pandas, NumPy, and mlpy * Predict the output of a power plant with regression models and forecast water flow of American rivers with time series methods using pandas, NumPy, Statsmodels, and scikit-learn * Explore social interactions and identify fraudulent activities with graph theory concepts using NetworkX and Gephi * Scrape Internet web pages using urlib and BeautifulSoup and get to know natural language processing techniques to classify movies ratings using NLTK * Study simulation techniques in an example of a gas station with agent-based modeling In Detail Data analysis is the process of systematically applying statistical and logical techniques to describe and illustrate, condense and recap, and evaluate data. Its importance has been most visible in the sector of information and communication technologies. It is an employee asset in almost all economy sectors. This book provides a rich set of independent recipes that dive into the world of data analytics and modeling using a variety of approaches, tools, and algorithms. You will learn the basics of data handling and modeling, and will build your skills gradually toward more advanced topics such as simulations, raw text processing, social interactions analysis, and more. First, you will learn some easy-to-follow practical techniques on how to read, write, clean, reformat, explore, and understand your data--arguably the most time-consuming (and the most important) tasks for any data scientist. In the second section, different independent recipes delve into intermediate topics such as classification, clustering, predicting, and more. With the help of these easy-to-follow recipes, you will also learn techniques that can easily be expanded to solve other real-life problems such as building recommendation engines or predictive models. In the third section, you will explore more advanced topics: from the field of graph theory through natural language processing, discrete choice modeling to simulations. You will also get to expand your knowledge on identifying fraud origin with the help of a graph, scrape Internet websites, and classify movies based on their reviews. By the end of this book, you will be able to efficiently use the vast array of tools that the Python environment has to offer. Style and approach This hands-on recipe guide is divided into three sections that tackle and overcome real-world data modeling problems faced by data analysts/scientist in their everyday work. Each independent recipe is written in an easy-to-follow and step-by-step fashion.
Practical Data Analysis Using Jupyter Notebook: Learn how to speak the language of data by extracting useful and actionable insights using Python
by Marc Wintjen Andrew VlahutinUnderstand data analysis concepts to make accurate decisions based on data using Python programming and Jupyter Notebook Key Features Find out how to use Python code to extract insights from data using real-world examples Work with structured data and free text sources to answer questions and add value using data Perform data analysis from scratch with the help of clear explanations for cleaning, transforming, and visualizing data Book Description Data literacy is the ability to read, analyze, work with, and argue using data. Data analysis is the process of cleaning and modeling your data to discover useful information. This book combines these two concepts by sharing proven techniques and hands-on examples so that you can learn how to communicate effectively using data. After introducing you to the basics of data analysis using Jupyter Notebook and Python, the book will take you through the fundamentals of data. Packed with practical examples, this guide will teach you how to clean, wrangle, analyze, and visualize data to gain useful insights, and you'll discover how to answer questions using data with easy-to-follow steps. Later chapters teach you about storytelling with data using charts, such as histograms and scatter plots. As you advance, you'll understand how to work with unstructured data using natural language processing (NLP) techniques to perform sentiment analysis. All the knowledge you gain will help you discover key patterns and trends in data using real-world examples. In addition to this, you will learn how to handle data of varying complexity to perform efficient data analysis using modern Python libraries. By the end of this book, you'll have gained the practical skills you need to analyze data with confidence. What you will learn Understand the importance of data literacy and how to communicate effectively using data Find out how to use Python packages such as NumPy, pandas, Matplotlib, and the Natural Language Toolkit (NLTK) for data analysis Wrangle data and create DataFrames using pandas Produce charts and data visualizations using time-series datasets Discover relationships and how to join data together using SQL Use NLP techniques to work with unstructured data to create sentiment analysis models Discover patterns in real-world datasets that provide accurate insights Who this book is for This book is for aspiring data analysts and data scientists looking for hands-on tutorials and real-world examples to understand data analysis concepts using SQL, Python, and Jupyter Notebook. Anyone looking to evolve their skills to become data-driven personally and professionally will also find this book useful. No prior knowledge of data analysis or programming is required to get started with this book.
Practical Data Analysis and Reporting with BIRT
by John WardThis book is a concise and practical guide aimed at getting the results you want as quickly as possible. It steers the reader through each point of reporting from setup, to scripting, designing, formatting, and deploying BIRT reports using a common example that runs through the book. This book is for Java developers who want to create rich reports and get started with BIRT to do this. Readers will need a basic understanding of SQL to follow along.