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Podcasts
New and developing technologies inevitably bring new types of malware with them, creating a huge demand for IT professionals that can keep malware at bay. With the help of this updated second edition of Mastering Malware Analysis, you’ll be able to add valuable reverse-engineering skills to your CV and learn how to protect organizations in the most efficient way.This book will familiarize you with multiple universal patterns behind different malicious software types and teach you how to analyze them using a variety of approaches.You'll learn how to examine malware code and determine the damage it can possibly cause to systems, along with ensuring that the right prevention or remediation steps are followed. As you cover all aspects of malware analysis for Windows, Linux, macOS, and mobile platforms in detail, you’ll also get to grips with obfuscation, anti-debugging, and other advanced anti-reverse-engineering techniques. The skills you acquire in this cybersecurity book will help you deal with all types of modern malware, strengthen your defenses, and prevent or promptly mitigate breaches regardless of the platforms involved.By the end of this book, you will have learned how to efficiently analyze samples, investigate suspicious activity, and build innovative solutions to handle malware incidents.
Matthias Marschall, John Ewart, Earl Waud
Chef is a configuration management tool that turns IT infrastructure into code. Chef provides tools to manage systems at scale. This learning path takes you on a comprehensive tour of Chef's functionality, ranging from its core features to advanced development. You will be brought up to speed with what's new in Chef and how to set up your own Chef infrastructure for individuals, or small or large teams. You will learn to use the basic Chef command-line tools. We will also take you through the core concepts of managing users, applications, and your entire cloud infrastructure. You will learn the techniques of the pros by walking you through a host of step-by-step guides to solve real-world infrastructure automation challenges.You will learn to automate and document every aspect of your network, from the hardware to software, middleware, and all your containers. You will become familiar with the Chef'sProvisioning tool. By the end of this course, you will be confident in how to manage your infrastructure, scale using the cloud, and extend the built-in functionality of Chef itself.The books used in this Learning Path are:1) Chef Essentials2)Chef Infrastructure Automation Cookbook – Second Edition3)Mastering Chef Provisioning
Beginning C++ Game Programming. Learn C++ from scratch and get started building your very own games
This book is all about offering you a fun introduction to the world of game programming, C++, and the OpenGL-powered SFML using three fun, fully-playable games. These games are an addictive frantic two-button tapper, a multi-level zombie survival shooter, and a split-screen multiplayer puzzle-platformer.We will start with the very basics of programming, such as variables, loops, and conditions and you will become more skillful with each game as you move through the key C++ topics, such as OOP (Object-Orientated Programming), C++ pointers, and an introduction to the Standard Template Library. While building these games, you will also learn exciting game programming concepts like particle effects, directional sound (spatialization), OpenGL programmable Shaders, spawning thousands of objects, and more.
Bayesian Analysis with Python. A practical guide to probabilistic modeling - Third Edition
Osvaldo Martin, Christopher Fonnesbeck, Thomas Wiecki
The third edition of Bayesian Analysis with Python serves as an introduction to the main concepts of applied Bayesian modeling using PyMC, a state-of-the-art probabilistic programming library, and other libraries that support and facilitate modeling like ArviZ, for exploratory analysis of Bayesian models; Bambi, for flexible and easy hierarchical linear modeling; PreliZ, for prior elicitation; PyMC-BART, for flexible non-parametric regression; and Kulprit, for variable selection.In this updated edition, a brief and conceptual introduction to probability theory enhances your learning journey by introducing new topics like Bayesian additive regression trees (BART), featuring updated examples. Refined explanations, informed by feedback and experience from previous editions, underscore the book's emphasis on Bayesian statistics. You will explore various models, including hierarchical models, generalized linear models for regression and classification, mixture models, Gaussian processes, and BART, using synthetic and real datasets.By the end of this book, you will possess a functional understanding of probabilistic modeling, enabling you to design and implement Bayesian models for your data science challenges. You'll be well-prepared to delve into more advanced material or specialized statistical modeling if the need arises.
Torque 3D is a popular game engine that supports you in every step along the way to making your game a reality. Even with all of the power and tools that Torque 3D provides, finishing a high quality 3D game requires time and knowledge.Torque 3D Game Development Cookbook is a practical guide that takes you through each of the major steps on the journey to creating your game, while learning a few tricks along the way.The recipes in this book start off with learning some of the finer points about TorqueScript. The book then moves on to each of Torque 3D's subsystems and ends with a variety of game play recipes.The various topics covered include activating level-specific game code and scheduling game events, dragging and dropping items between windows to work with an in-game inventory system, and covering the seams between objects with well placed decals. Some of the advanced topics include writing custom shaders and postFX, using zones to improve rendering performance, and enhancing your game's ambience through sound.Once you are done with Torque 3D Game Development Cookbook you'll be on your way to creating amazing 3D games and gain expert knowledge of Torque 3D.
Willi Richert, Luis Pedro Coelho
Machine learning, the field of building systems that learn from data, is exploding on the Web and elsewhere. Python is a wonderful language in which to develop machine learning applications. As a dynamic language, it allows for fast exploration and experimentation and an increasing number of machine learning libraries are developed for Python.Building Machine Learning system with Python shows you exactly how to find patterns through raw data. The book starts by brushing up on your Python ML knowledge and introducing libraries, and then moves on to more serious projects on datasets, Modelling, Recommendations, improving recommendations through examples and sailing through sound and image processing in detail. Using open-source tools and libraries, readers will learn how to apply methods to text, images, and sounds. You will also learn how to evaluate, compare, and choose machine learning techniques. Written for Python programmers, Building Machine Learning Systems with Python teaches you how to use open-source libraries to solve real problems with machine learning. The book is based on real-world examples that the user can build on.Readers will learn how to write programs that classify the quality of StackOverflow answers or whether a music file is Jazz or Metal. They will learn regression, which is demonstrated on how to recommend movies to users. Advanced topics such as topic modeling (finding a text's most important topics), basket analysis, and cloud computing are covered as well as many other interesting aspects.Building Machine Learning Systems with Python will give you the tools and understanding required to build your own systems, which are tailored to solve your problems.