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Podcasty
Claudio Stamile, Aldo Marzullo, Enrico Deusebio
Graph Machine Learning will introduce you to a set of tools used for processing network data and leveraging the power of the relation between entities that can be used for predictive, modeling, and analytics tasks. The first chapters will introduce you to graph theory and graph machine learning, as well as the scope of their potential use. You’ll then learn all you need to know about the main machine learning models for graph representation learning: their purpose, how they work, and how they can be implemented in a wide range of supervised and unsupervised learning applications. You'll build a complete machine learning pipeline, including data processing, model training, and prediction in order to exploit the full potential of graph data. After covering the basics, you’ll be taken through real-world scenarios such as extracting data from social networks, text analytics, and natural language processing (NLP) using graphs and financial transaction systems on graphs. You’ll also learn how to build and scale out data-driven applications for graph analytics to store, query, and process network information, and explore the latest trends on graphs. By the end of this machine learning book, you will have learned essential concepts of graph theory and all the algorithms and techniques used to build successful machine learning applications.
Serverless computing is a way to run your code without having to provision or manage servers. Amazon Web Services provides serverless services that you can use to build and deploy cloud-native applications. Starting with the basics of AWS Lambda, this book takes you through combining Lambda with other services from AWS, such as Amazon API Gateway, Amazon DynamoDB, and Amazon Step Functions. You’ll learn how to write, run, and test Lambda functions using examples in Node.js, Java, Python, and C# before you move on to developing and deploying serverless APIs efficiently using the Serverless Framework. In the concluding chapters, you’ll discover tips and best practices for leveraging Serverless Framework to increase your development productivity. By the end of this book, you’ll have become well-versed in building, securing, and running serverless applications using Amazon API Gateway and AWS Lambda without having to manage any servers.
IBM Cognos 10 BI is the leader in the Gartner quadrant in terms of BI capabilities. There have been new features introduced with IBM Cognos 10 BI in terms of dashboards and BI. The book intends to highlight the latest and advanced dashboarding features introduced with IBM Cognos 10 BI. The book covers Business Insight and Business Insight Advanced in a comprehensive manner. It also covers best practices in terms of creating and distributing dashboards using IBM Cognos 10 BI, without which no BI solution would look presentable, usable and efficient. The book covers the new IBM Cognos 10 dashboarding capabilities in detail and a comprehensive manner. There whole content is divided in to step-by-step recipes, each of which covers a specific link in the whole chain of understanding and learning.Recipes are augmented with real steps and screenshots which nullify chances of error or misjudgement.These along with explanation, tips and information will help users to completely follow recipes and have a clear and concise understanding and will eventually enable them to use these in their own areas of interest.
Liyanapathirannahelage H Perera
MapReduce is a technology that enables users to process large datasets and Hadoop is an implementation of MapReduce. We are beginning to see more and more data becoming available, and this hides many insights that might hold key to success or failure. However, MapReduce has the ability to analyze this data and write code to process it.Instant MapReduce Patterns – Hadoop Essentials How-to is a concise introduction to Hadoop and programming with MapReduce. It is aimed to get you started and give you an overall feel for programming with Hadoop so that you will have a well-grounded foundation to understand and solve all of your MapReduce problems as needed.Instant MapReduce Patterns – Hadoop Essentials How-to will start with the configuration of Hadoop before moving on to writing simple examples and discussing MapReduce programming patterns.We will start simply by installing Hadoop and writing a word count program. After which, we will deal with the seven styles of MapReduce programs: analytics, set operations, cross correlation, search, graph, Joins, and clustering. For each case, you will learn the pattern and create a representative example program. The book also provides you with additional pointers to further enhance your Hadoop skills.
With the latest updates and revised study material, this second edition of the Certified Information Systems Auditor Study Guide provides an excellent starting point for your CISA certification preparation. The book strengthens your grip on the core concepts through a three-step approach. First, it presents the fundamentals with easy-to-understand theoretical explanations. Next, it provides a list of key aspects that are crucial from the CISA exam perspective, ensuring you focus on important pointers for the exam. Finally, the book makes you an expert in specific topics by engaging you with self-assessment questions designed to align with the exam format, challenging you to apply your knowledge and sharpen your understanding.Moreover, the book comes with lifetime access to supplementary resources on an online platform, including CISA flashcards, practice questions, and valuable exam tips. With unlimited access to the website, you’ll have the flexibility to practice as many times as you desire, maximizing your exam readiness.By the end of this book, you’ll have developed the proficiency to successfully obtain the CISA certification and significantly upgrade your auditing career.
Malware Analysis Techniques. Tricks for the triage of adversarial software
Malicious software poses a threat to every enterprise globally. Its growth is costing businesses millions of dollars due to currency theft as a result of ransomware and lost productivity. With this book, you'll learn how to quickly triage, identify, attribute, and remediate threats using proven analysis techniques. Malware Analysis Techniques begins with an overview of the nature of malware, the current threat landscape, and its impact on businesses. Once you've covered the basics of malware, you'll move on to discover more about the technical nature of malicious software, including static characteristics and dynamic attack methods within the MITRE ATT&CK framework. You'll also find out how to perform practical malware analysis by applying all that you've learned to attribute the malware to a specific threat and weaponize the adversary's indicators of compromise (IOCs) and methodology against them to prevent them from attacking. Finally, you'll get to grips with common tooling utilized by professional malware analysts and understand the basics of reverse engineering with the NSA's Ghidra platform. By the end of this malware analysis book, you’ll be able to perform in-depth static and dynamic analysis and automate key tasks for improved defense against attacks.
Causal methods present unique challenges compared to traditional machine learning and statistics. Learning causality can be challenging, but it offers distinct advantages that elude a purely statistical mindset. Causal Inference and Discovery in Python helps you unlock the potential of causality.You’ll start with basic motivations behind causal thinking and a comprehensive introduction to Pearlian causal concepts, such as structural causal models, interventions, counterfactuals, and more. Each concept is accompanied by a theoretical explanation and a set of practical exercises with Python code. Next, you’ll dive into the world of causal effect estimation, consistently progressing towards modern machine learning methods. Step-by-step, you’ll discover Python causal ecosystem and harness the power of cutting-edge algorithms. You’ll further explore the mechanics of how “causes leave traces” and compare the main families of causal discovery algorithms. The final chapter gives you a broad outlook into the future of causal AI where we examine challenges and opportunities and provide you with a comprehensive list of resources to learn more.By the end of this book, you will be able to build your own models for causal inference and discovery using statistical and machine learning techniques as well as perform basic project assessment.
This guide demonstrates just how easy it is to get started with QlikView and create your own BI application. Featuring an introduction to its core features before exploring how to load data and model it, you’ll soon become more confident that you can take full advantage of QlikView’s capabilities.. You will also learn how to use QVD files with QlikView – and how they offer a simpler way of handling data.After digging deeper into data handling, as you learn how to use mapping tables and create a master calendar, you’ll then find out how to get the most from QlikView’s visualization features – vital if you are to use your data insights effectively. From accessible and user friendly dashboards to strategies and best practices for subjecting data to further analysis, you can be confident that you’ll be prepared to get the most out of your data with QlikView.With details on how to finally secure your application and deploy it for a successful integration in your organization, QlikView Essentials underlines exactly why QlikView is becoming more and more popular for businesses that understand the value of data.
Simone Onofri, Donato Onofri, Matteo Meucci
Web attacks and exploits pose an ongoing threat to the interconnected world. This comprehensive book explores the latest challenges in web application security, providing you with an in-depth understanding of hackers' methods and the practical knowledge and skills needed to effectively understand web attacks.The book starts by emphasizing the importance of mindset and toolset in conducting successful web attacks. You’ll then explore the methodologies and frameworks used in these attacks, and learn how to configure the environment using interception proxies, automate tasks with Bash and Python, and set up a research lab. As you advance through the book, you’ll discover how to attack the SAML authentication layer; attack front-facing web applications by learning WordPress and SQL injection, and exploit vulnerabilities in IoT devices, such as command injection, by going through three CTFs and learning about the discovery of seven CVEs. Each chapter analyzes confirmed cases of exploitation mapped with MITRE ATT&CK. You’ll also analyze attacks on Electron JavaScript-based applications, such as XSS and RCE, and the security challenges of auditing and exploiting Ethereum smart contracts written in Solidity. Finally, you’ll find out how to disclose vulnerabilities.By the end of this book, you’ll have enhanced your ability to find and exploit web vulnerabilities.
Supervised machine learning is used in a wide range of sectors, such as finance, online advertising, and analytics, to train systems to make pricing predictions, campaign adjustments, customer recommendations, and much more by learning from the data that is used to train it and making decisions on its own. This makes it crucial to know how a machine 'learns' under the hood.This book will guide you through the implementation and nuances of many popular supervised machine learning algorithms, and help you understand how they work. You’ll embark on this journey with a quick overview of supervised learning and see how it differs from unsupervised learning. You’ll then explore parametric models, such as linear and logistic regression, non-parametric methods, such as decision trees, and a variety of clustering techniques that facilitate decision-making and predictions. As you advance, you'll work hands-on with recommender systems, which are widely used by online companies to increase user interaction and enrich shopping potential. Finally, you’ll wrap up with a brief foray into neural networks and transfer learning.By the end of this book, you’ll be equipped with hands-on techniques and will have gained the practical know-how you need to quickly and effectively apply algorithms to solve new problems.
Automating Security Detection Engineering. A hands-on guide to implementing Detection as Code
Today's global enterprise security programs grapple with constantly evolving threats. Even though the industry has released abundant security tools, most of which are equipped with APIs for integrations, they lack a rapid detection development work stream. This book arms you with the skills you need to automate the development, testing, and monitoring of detection-based use cases.You’ll start with the technical architecture, exploring where automation is conducive throughout the detection use case lifecycle. With the help of hands-on labs, you’ll learn how to utilize threat-informed defense artifacts and then progress to creating advanced AI-powered CI/CD pipelines to bolster your Detection as Code practices. Along the way, you'll develop custom code for EDRs, WAFs, SIEMs, CSPMs, RASPs, and NIDS. The book will also guide you in developing KPIs for program monitoring and cover collaboration mechanisms to operate the team with DevSecOps principles. Finally, you'll be able to customize a Detection as Code program that fits your organization's needs.By the end of the book, you'll have gained the expertise to automate nearly the entire use case development lifecycle for any enterprise.
Elasticsearch is a Lucene-based distributed search server that allows users to index and search unstructured content with petabytes of data. With this book, you'll be guided through comprehensive recipes on what's new in Elasticsearch 7, and see how to create and run complex queries and analytics.Packed with recipes on performing index mapping, aggregation, and scripting using Elasticsearch, this fourth edition of Elasticsearch Cookbook will get you acquainted with numerous solutions and quick techniques for performing both every day and uncommon tasks such as deploying Elasticsearch nodes, integrating other tools to Elasticsearch, and creating different visualizations. You will install Kibana to monitor a cluster and also extend it using a variety of plugins. Finally, you will integrate your Java, Scala, Python, and big data applications such as Apache Spark and Pig with Elasticsearch, and create efficient data applications powered by enhanced functionalities and custom plugins.By the end of this book, you will have gained in-depth knowledge of implementing Elasticsearch architecture, and you'll be able to manage, search, and store data efficiently and effectively using Elasticsearch.
Ryan Mangan, Neil McLoughlin, Marcel Meurer, Christiaan Brinkhoff
Acquire in-depth knowledge for designing, building, and supporting Azure Virtual Desktop environments with the updated second edition of Mastering Azure Virtual Desktop. With content aligned with exam objectives, this book will help you ace the Microsoft AZ-140 exam.This book starts with an introduction to Azure Virtual Desktop before delving into the intricacies of planning and architecting its infrastructure. As you progress, you’ll learn about the implementation process, with an emphasis on best practices and effective strategies. You’ll explore key areas such as managing and controlling access, advanced monitoring with the new Azure Monitoring Agent, and advanced application deployment. You’ll also gain hands-on experience with essential features like the MSIX app attach, enhancing user experience and operational efficiency. Beyond advancing your skills, this book is a crucial resource for those preparing for the Microsoft Certified: Azure Virtual Desktop Specialty certification.By the end of this book, you’ll have a thorough understanding of the Azure Virtual Desktop environment, from design to implementation.
Java Deep Learning Essentials. Unlocking the next generation of predictive power
AI and Deep Learning are transforming the way we understand software, making computers more intelligent than we could even imagine just a decade ago. Deep Learning algorithms are being used across a broad range of industries – as the fundamental driver of AI, being able to tackle Deep Learning is going to a vital and valuable skill not only within the tech world but also for the wider global economy that depends upon knowledge and insight for growth and success. It’s something that’s moving beyond the realm of data science – if you’re a Java developer, this book gives you a great opportunity to expand your skillset.Starting with an introduction to basic machine learning algorithms, to give you a solid foundation, Deep Learning with Java takes you further into this vital world of stunning predictive insights and remarkable machine intelligence. Once you’ve got to grips with the fundamental mathematical principles, you’ll start exploring neural networks and identify how to tackle challenges in large networks using advanced algorithms. You will learn how to use the DL4J library and apply Deep Learning to a range of real-world use cases. Featuring further guidance and insights to help you solve challenging problems in image processing, speech recognition, language modeling, this book will make you rethink what you can do with Java, showing you how to use it for truly cutting-edge predictive insights. As a bonus, you’ll also be able to get to grips with Theano and Caffe, two of the most important tools in Deep Learning today.By the end of the book, you’ll be ready to tackle Deep Learning with Java. Wherever you’ve come from – whether you’re a data scientist or Java developer – you will become a part of the Deep Learning revolution!