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The Art of Mac Malware
The Art of Mac Malware

Defenders must fully understand how malicious software works if they hope to stay ahead of the increasingly sophisticated threats facing Apple products today. The Art of Mac Malware: The Guide to Analyzing Malicious Software is a comprehensive handbook to cracking open these malicious programs and seeing what's inside. Discover the secrets of nation state backdoors, destructive ransomware, and subversive cryptocurrency miners as you uncover their infection methods, persistence strategies, and insidious capabilities. Then work with and extend foundational reverse-engineering tools to extract and decrypt embedded strings, unpack protected Mach-O malware, and even reconstruct binary code. Next, using a debugger, you'll execute the malware, instruction by instruction, to discover exactly how it operates. In the book's final section, you'll put these lessons into practice by analyzing a complex Mac malware specimen on your own. A former NSA hacker and current leader in the field of ma ...
Keras Succinctly
Keras Succinctly

Neural networks are a powerful tool for developers, but harnessing them can be a challenge. With Keras Succinctly, author James McCaffrey introduces Keras, an open-source, neural network library designed specifically to make working with backend neural network tools easier. ...
TensorFlow in Action
TensorFlow in Action

In TensorFlow in Action, you'll dig into the newest version of Google's amazing TensorFlow framework as you learn to create incredible deep learning applications. Author Thushan Ganegedara uses quirky stories, practical examples, and behind-the-scenes explanations to demystify concepts otherwise trapped in dense academic papers. As you dive into modern deep learning techniques like transformer and attention models, you'll benefit from the unique insights of a top StackOverflow contributor for deep learning and NLP. Google's TensorFlow framework sits at the heart of modern deep learning. Boasting practical features like multi-GPU support, network data visualization, and easy production pipelines using TensorFlow Extended (TFX), TensorFlow provides the most efficient path to professional AI applications. And the Keras library, fully integrated into TensorFlow 2, makes it a snap to build and train even complex models for vision, language, and more. TensorFlow in Action teaches you t ...
Genomics in the Azure Cloud
Genomics in the Azure Cloud

This practical guide bridges the gap between general cloud computing architecture in Microsoft Azure and scientific computing for bioinformatics and genomics. You'll get a solid understanding of the architecture patterns and services that are offered in Azure and how they might be used in your bioinformatics practice. You'll get code examples that you can reuse for your specific needs. And you'll get plenty of concrete examples to illustrate how a given service is used in a bioinformatics context. You'll also get valuable advice on how to: Use enterprise platform services to easily scale your bioinformatics workloads; Organize, query, and analyze genomic data at scale; Build a genomics data lake and accompanying data warehouse; Use Azure Machine Learning to scale your model training, track model performance, and deploy winning models; Orchestrate and automate processing pipelines using Azure Data Factory and Databricks; Cloudify your organization's existing bioinformatics pipelines ...
Applying Math with Python, 2nd Edition
Applying Math with Python, 2nd Edition

The updated edition of Applying Math with Python will help you solve complex problems in a wide variety of mathematical fields in simple and efficient ways. Old recipes have been revised for new libraries and several recipes have been added to demonstrate new tools such as JAX. You'll start by refreshing your knowledge of several core mathematical fields and learn about packages covered in Python's scientific stack, including NumPy, SciPy, and Matplotlib. As you progress, you'll gradually get to grips with more advanced topics of calculus, probability, and networks (graph theory). Once you've developed a solid base in these topics, you'll have the confidence to set out on math adventures with Python as you explore Python's applications in data science and statistics, forecasting, geometry, and optimization. The final chapters will take you through a collection of miscellaneous problems, including working with specific data formats and accelerating code. By the end of this book, y ...
Geospatial Analysis with SQL
Geospatial Analysis with SQL

Geospatial analysis is industry agnostic and a powerful tool for answering location questions. Combined with the power of SQL, developers and analysts worldwide rely on database integration to solve real-world spatial problems. This book introduces skills to help you detect and quantify patterns in datasets through data exploration, visualization, data engineering, and the application of analysis and spatial techniques. You will begin by exploring the fundamentals of geospatial analysis where you'll learn about the importance of geospatial analysis and how location information enhances data exploration. Walter Tobler's second law of geography states, "the phenomenon external to a geographic area of interest affects what goes on inside." This quote will be the framework of the geospatial questions we will explore. You'll then observe the framework of geospatial analysis using SQL while learning to create spatial databases and SQL queries and functions. By the end of this book, you will ...
An Introduction to C & GUI Programming, 2nd Edition
An Introduction to C & GUI Programming, 2nd Edition

Freshly updated for GTK3, the 2nd edition of An Introduction to C & GUI Programming will teach you all you need to know to write simple programs in C and start creating GUIs, even if you're an absolute beginner. The first half of the book is an introduction to C, and covers the basics of writing simple command-line programs. The second half shows how to use the GTK user interface toolkit with C to create feature-rich GUI applications which can be run on the desktop. 156 pages of essential information: - Create simple command-line C programs - Control flow with conditions and loops - Handle variables, strings, and files - Design graphical user interface applications in C - Handle user input with buttons and menus - Use advanced UI features such as data stores and dialogs ...
Learning Informatica PowerCenter 9.x
Learning Informatica PowerCenter 9.x

Informatica PowerCenter provides the perfect platform to utilize and leverage business data. It allows you to easily, conveniently, and efficiently work on different types of data. This book covers functionality such as creating/importing source and target, identifying errors, and debugging your mapping through a series of comprehensive tutorials. Besides learning about types of Slowly Changing Dimensions (SCDs), you will learn to create and link workflows. As you progress, exhaustive knowledge of transformations and techniques to create folders, migrate code, and optimize system performance will be explored in detail. The step-by-step approach and adoption of real-time scenarios will guide you through effectively accessing all core functionalities offered by Informatica PowerCenter. ...
Modern Data Mining Algorithms in C++ and CUDA C
Modern Data Mining Algorithms in C++ and CUDA C

Discover a variety of data-mining algorithms that are useful for selecting small sets of important features from among unwieldy masses of candidates, or extracting useful features from measured variables. As a serious data miner you will often be faced with thousands of candidate features for your prediction or classification application, with most of the features being of little or no value. You'll know that many of these features may be useful only in combination with certain other features while being practically worthless alone or in combination with most others. Some features may have enormous predictive power, but only within a small, specialized area of the feature space. The problems that plague modern data miners are endless. This book helps you solve this problem by presenting modern feature selection techniques and the code to implement them. Some of these techniques are: Forward selection component analysis; Local feature selection; Linking features and a target with a h ...
Data-Driven Alexa Skills
Data-Driven Alexa Skills

Design and build innovative, custom, data-driven Alexa skills for home or business. Working through several projects, this book teaches you how to build Alexa skills and integrate them with online APIs. If you have basic Python skills, this book will show you how to build data-driven Alexa skills. You will learn to use data to give your Alexa skills dynamic intelligence, in-depth knowledge, and the ability to remember. Data-Driven Alexa Skills takes a step-by-step approach to skill development. You will begin by configuring simple skills in the Alexa Skill Builder Console. Then you will develop advanced custom skills that use several Alexa Skill Development Kit features to integrate with lambda functions, Amazon Web Services (AWS), and Internet data feeds. These advanced skills enable you to link user accounts, query and store data using a NoSQL database, and access real estate listings and stock prices via web APIs. ...
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