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Podcasts
Remote working has given hackers plenty of opportunities as more confidential information is shared over the internet than ever before. In this new edition of Mastering Kali Linux for Advanced Penetration Testing, you’ll learn an offensive approach to enhance your penetration testing skills by testing the sophisticated tactics employed by real hackers. You’ll go through laboratory integration to cloud services so that you learn another dimension of exploitation that is typically forgotten during a penetration test. You'll explore different ways of installing and running Kali Linux in a VM and containerized environment and deploying vulnerable cloud services on AWS using containers, exploiting misconfigured S3 buckets to gain access to EC2 instances. This book delves into passive and active reconnaissance, from obtaining user information to large-scale port scanning. Building on this, different vulnerability assessments are explored, including threat modeling. See how hackers use lateral movement, privilege escalation, and command and control (C2) on compromised systems. By the end of this book, you’ll have explored many advanced pentesting approaches and hacking techniques employed on networks, IoT, embedded peripheral devices, and radio frequencies.
This book is packed with easy-to-follow guidelines that explain the workings of the many key data mining tools of R, which are used to discover knowledge from your data.You will learn how to perform key predictive analytics tasks using R, such as train and test predictive models for classification and regression tasks, score new data sets and so on. All chapters will guide you in acquiring the skills in a practical way. Most chapters also include a theoretical introduction that will sharpen your understanding of the subject matter and invite you to go further.The book familiarizes you with the most common data mining tools of R, such as k-means, hierarchical regression, linear regression, association rules, principal component analysis, multilevel modeling, k-NN, Naïve Bayes, decision trees, and text mining. It also provides a description of visualization techniques using the basic visualization tools of R as well as lattice for visualizing patterns in data organized in groups. This book is invaluable for anyone fascinated by the data mining opportunities offered by GNU R and its packages.
Generative AI Art. Unleash Your Creativity with Generative AI Art for Beginners
The course introduces the basic concepts of artificial intelligence and its application in art, making it accessible even to those without a technical background. This foundation paves the way for exploring the nuances of effective prompt crafting, a critical skill for generating bespoke AI artwork.The course focuses on hands-on demonstrations with leading AI art software, including Craiyon and Midjourney, offering step-by-step guides to harness these tools effectively. Through practical examples, learners will understand how to navigate image prompts, masking techniques, framing, and lighting to enhance the visual appeal of their creations. The significance of navigating these elements is underscored, highlighting their role in achieving consistency and originality in AI-generated art.The course wraps up by delving into the remixing of popular art styles, the art of creating compelling text prompts, and the critical aspects of image rights, ethics, privacy, and originality in the digital art space. By concluding with recommended resources, learners are equipped to continue their journey in AI art, fueled by inspiration and a solid understanding of the field's possibilities and responsibilities.
If data is the new oil, then machine learning is the drill. As companies gain access to ever-increasing quantities of raw data, the ability to deliver state-of-the-art predictive models that support business decision-making becomes more and more valuable.In this book, you’ll work on an end-to-end project based around a realistic data set and split up into bite-sized practical exercises. This creates a case-study approach that simulates the working conditions you’ll experience in real-world data science projects.You’ll learn how to use key Python packages, including pandas, Matplotlib, and scikit-learn, and master the process of data exploration and data processing, before moving on to fitting, evaluating, and tuning algorithms such as regularized logistic regression and random forest. Now in its second edition, this book will take you through the end-to-end process of exploring data and delivering machine learning models. Updated for 2021, this edition includes brand new content on XGBoost, SHAP values, algorithmic fairness, and the ethical concerns of deploying a model in the real world.By the end of this data science book, you’ll have the skills, understanding, and confidence to build your own machine learning models and gain insights from real data.
In an era marked by a growing demand for tech solutions and a shortage of skilled developers, companies grapple with hiring expenses. No-code tools offer a faster, more affordable software development alternative. Leading this no-code revolution is Bubble, enabling newcomers to construct impressive web applications in a matter of weeks if not days.Written by Caio Calderari, a seasoned no-code expert with 17 years of experience to offers practical advice for mastering no-code application development. You'll learn to plan your app with Bubble's visual builder features and UI components and implement frontend functionalities such as customizing layouts and creating responsive user interfaces. The book covers workflow automation, database management, security best practices, and backend functionality setup and advances to span the Bubble plugin ecosystem and API integration for third-party services to improve the app's functionality. Additionally, you'll explore app testing, debugging, performance monitoring, and maintenance. From launching with a custom domain to gathering user feedback for continuous improvement and optimization of performance and scalability, you’ll learn every aspect of Bubble's app development and deployment.By the end of this book, you'll know how to bring your digital ideas to life without writing code.
TypeScript is an open source and cross-platform statically typed superset of JavaScript that compiles to plain JavaScript and runs in any browser or host. This book is a step-by-step guide that will take you through the use and benefits of TypeScript with the help of practical examples. You will start off by understanding the basics as well as the new features of TypeScript 2.x. Then, you will learn how to work with functions and asynchronous programming APIs. You will continue by learning how to resolve runtime issues and how to implement TypeScript applications using the Object-oriented programming (OOP) and functional programming (FP) paradigms. Later, you will automate your development workflow with the help of tools such as Webpack. Towards the end of this book, you will delve into some real-world scenarios by implementing some full-stack TypeScript applications with Node.js, React and Angular as well as how to optimize and test them. Finally, you will be introduced to the internal APIs of the TypeScript compiler, and you will learn how to create custom code analysis tools.