BackTrack 5 Wireless Penetration Testing Beginner's Guide. Master bleeding edge wireless testing techniques with BackTrack 5

Vivek Ramachandran

Wireless has become ubiquitous in today’s world. The mobility and flexibility provided by it makes our lives more comfortable and productive. But this comes at a cost – Wireless technologies are inherently insecure and can be easily broken. BackTrack is a penetration testing and security auditing distribution that comes with a myriad of wireless networking tools used to simulate network attacks and detect security loopholes. Backtrack 5 Wireless Penetration Testing Beginner’s Guide will take you through the journey of becoming a Wireless hacker. You will learn various wireless testing methodologies taught using live examples, which you will implement throughout this book. The engaging practical sessions very gradually grow in complexity giving you enough time to ramp up before you get to advanced wireless attacks.This book will take you through the basic concepts in Wireless and creating a lab environment for your experiments to the business of different lab sessions in wireless security basics, slowly turn on the heat and move to more complicated scenarios, and finally end your journey by conducting bleeding edge wireless attacks in your lab.There are many interesting and new things that you will learn in this book – War Driving, WLAN packet sniffing, Network Scanning, Circumventing hidden SSIDs and MAC filters, bypassing Shared Authentication, Cracking WEP and WPA/WPA2 encryption, Access Point MAC spoofing, Rogue Devices, Evil Twins, Denial of Service attacks, Viral SSIDs, Honeypot and Hotspot attacks, Caffe Latte WEP Attack, Man-in-the-Middle attacks, Evading Wireless Intrusion Prevention systems and a bunch of other cutting edge wireless attacks.If you were ever curious about what wireless security and hacking was all about, then this book will get you started by providing you with the knowledge and practical know-how to become a wireless hacker.

The Ultimate Guide to Snowpark. Design and deploy Snowflake Snowpark with Python for efficient data workloads

Shankar Narayanan SGS, Vivekanandan SS, Jeff Hollan

Snowpark is a powerful framework that helps you unlock numerous possibilities within the Snowflake Data Cloud. However, without proper guidance, leveraging the full potential of Snowpark with Python can be challenging. Packed with practical examples and code snippets, this book will be your go-to guide to using Snowpark with Python successfully.The Ultimate Guide to Snowpark helps you develop an understanding of Snowflake Snowpark and how it enables you to implement workloads in data engineering, data science, and data applications within the Data Cloud. From configuration and coding styles to workloads such as data manipulation, collection, preparation, transformation, aggregation, and analysis, this guide will equip you with the right knowledge to make the most of this framework. You'll discover how to build, test, and deploy data pipelines and data science models. As you progress, you’ll deploy data applications natively in Snowflake and operate large language models (LLMs) using Snowpark container services.By the end of this book, you'll be able to leverage Snowpark's capabilities and propel your career as a Snowflake developer to new heights.

Strategic Leadership in Responsive Web Design. A tech leader's guide to achieving business excellence by adopting responsive web design

Harley Ferguson

Strategic Leadership in Responsive Web Design is an essential guide that will equip you with the knowledge and foresight needed to navigate the ever-evolving digital landscape.You’ll start by learning about the strategic importance of responsive web design (RWD) before delving into its intricacies. As you progress, you’ll not only discover the technical aspects of adaptive design, but also learn how to seamlessly integrate these principles within your organization’s business objectives. You’ll develop the skills required to integrate RWD principles into broader business goals. Next, you’ll learn how to navigate SEO in modern times while ensuring platforms are consistent in design across devices. Later, this book shows you how to measure the ROI when making RWD decisions, and how to ensure you’re making the right one.By the end of this book, you’ll have understood the role that RWD plays in achieving broad business objectives.

Hands-On Deep Learning Algorithms with Python. Master deep learning algorithms with extensive math by implementing them using TensorFlow

Sudharsan Ravichandiran

Deep learning is one of the most popular domains in the AI space that allows you to develop multi-layered models of varying complexities. This book introduces you to popular deep learning algorithms—from basic to advanced—and shows you how to implement them from scratch using TensorFlow. Throughout the book, you will gain insights into each algorithm, the mathematical principles involved, and how to implement it in the best possible manner. The book starts by explaining how you can build your own neural networks, followed by introducing you to TensorFlow, the powerful Python-based library for machine learning and deep learning. Moving on, you will get up to speed with gradient descent variants, such as NAG, AMSGrad, AdaDelta, Adam, and Nadam. The book will then provide you with insights into recurrent neural networks (RNNs) and LSTM and how to generate song lyrics with RNN. Next, you will master the math necessary to work with convolutional and capsule networks, widely used for image recognition tasks. You will also learn how machines understand the semantics of words and documents using CBOW, skip-gram, and PV-DM. Finally, you will explore GANs, including InfoGAN and LSGAN, and autoencoders, such as contractive autoencoders and VAE. By the end of this book, you will be equipped with all the skills you need to implement deep learning in your own projects.

Asterisk 1.4 - The Professional's Guide. Implementing, Administering, and Consulting on Commercial IP Telephony Solutions

Colman Carpenter, David Duffett, Ian Plain, Nik Middleton, ...

Asterisk is the leading Open Source Telephony application and PBX software solution. It represents an effective, easy-to-administer, and accessible platform for running enterprise telephony requirements. The real world, however, offers numerous hurdles when running Asterisk in the commercial environment including call routing, resilience, or integrating Asterisk with other systems. This book will show you some of the ways to overcome these problems.As the follow-up to Packt's highly successful 2005 title Building Telephony Systems with Asterisk, this book presents the collected wisdom of Asterisk Professionals in the commercial environment.Aimed at Administrators and Asterisk Consultants who are comfortable with the basics of Asterisk operation and installation, this book covers numerous hands-on topics such as Call Routing, Network Considerations, Scalability, and Resilience ñ all the while providing practical solutions and suggestions. It also covers more business-related areas like Billing Solutions and a Winning Sales Technique. Even if your interest or experience with Asterisk is lower level, this book will provide a deeper understanding of how Asterisk operates in the real world.Asterisk is deployed across countless enterprises globally. Running on Linux, it has constantly demonstrated its resilience, stability, and scalability and is now the advanced communication solution of choice to many organizations and consultants.With a foreword from Mark Spencer, the man behind Asterisk, this book presents the accumulated wisdom of three leading Asterisk Consultants and shows the reader how to get the most out of Asterisk in the commercial environment. Over the course of eleven chapters, this book introduces the reader to topics as diverse as Advanced Dial Plans, Network Considerations, and Call Routing, through to Localization, DAHDI, Speech Technology, and Working with a GUI. The book also covers the more nebulous aspects of being an Asterisk professional such as evaluating customer requirements and pitching for contracts.This book represents the wisdom and thoughts of front line consultants. The knowledge they impart will prove informative, thought provoking and be of lasting interest to Asterisk professionals.

OData Programming Cookbook for .NET Developers. 70 fast-track, example-driven recipes with clear instructions and details for OData programming with .NET Framework with this book and

Steven Cheng, Juntao Cheng

Odata (Open Data Protocol) is a Web protocol for querying and updating data that provides a way to unlock your data and free it from silos that exist in applications today. OData enables data access among a variety of applications, services, and stores by adopting existing Web technologies such as HTTP, XML, and JSON. This book deals with common OData programming cases over the Microsoft .NET Framework platform and eases the learning curve for a .NET developer to start incorporating OData in data service development.This book provides a collection of recipes that help .NET developers to get familiar with OData programming in a quick and efficient manner. The recipes cover most OData features from the former ADO.NET Data Service to the current WCF Data Service platform. In addition, all the sample cases here are based on real-world scenarios and issues that .NET developers might come across when programming with OData in application development.This book will be your handy guide with basic to advanced walkthroughs of common OData programming cases for the Microsoft .NET Framework platform. You will learn quick solutions to necessary tasks to integrate the power of OData at both server-side and client-side.This book will help you master the use of OData with .NET Framework by taking you through hands-on and practical recipes. It starts by talking about the common means for building OData services and consuming OData services in client applications. Then, some more specific topics like hosting, configuration and security are discussed. The book also covers many popular and interesting topics such as integrating OData in web applications, and developing data-driven mobile applications with OData. Moreover, you can also find quite a few recipes discussing real-world OData producers and new features in latest and future versions.Within OData Programming Cookbook for .NET Developers, all the recipes are selected based on real-world scenarios that you will commonly come across. Each recipe covers a specific topic, going from the description of the problem, through a conceptual solution, to a solution containing sample code. By following these recipes, you can acquire how to program with OData in a simple, effective, and easy manner.

Python Feature Engineering Cookbook. A complete guide to crafting powerful features for your machine learning models - Third Edition

Soledad Galli, Christoph Molnar

Streamline data preprocessing and feature engineering in your machine learning project with this third edition of the Python Feature Engineering Cookbook to make your data preparation more efficient.This guide addresses common challenges, such as imputing missing values and encoding categorical variables using practical solutions and open source Python libraries. You’ll learn advanced techniques for transforming numerical variables, discretizing variables, and dealing with outliers. Each chapter offers step-by-step instructions and real-world examples, helping you understand when and how to apply various transformations for well-prepared data.The book explores feature extraction from complex data types such as dates, times, and text. You’ll see how to create new features through mathematical operations and decision trees and use advanced tools like Featuretools and tsfresh to extract features from relational data and time series.By the end, you’ll be ready to build reproducible feature engineering pipelines that can be easily deployed into production, optimizing data preprocessing workflows and enhancing machine learning model performance.

The Machine Learning Solutions Architect Handbook. Create machine learning platforms to run solutions in an enterprise setting

David Ping

When equipped with a highly scalable machine learning (ML) platform, organizations can quickly scale the delivery of ML products for faster business value realization. There is a huge demand for skilled ML solutions architects in different industries, and this handbook will help you master the design patterns, architectural considerations, and the latest technology insights you’ll need to become one. You’ll start by understanding ML fundamentals and how ML can be applied to solve real-world business problems. Once you've explored a few leading problem-solving ML algorithms, this book will help you tackle data management and get the most out of ML libraries such as TensorFlow and PyTorch. Using open source technology such as Kubernetes/Kubeflow to build a data science environment and ML pipelines will be covered next, before moving on to building an enterprise ML architecture using Amazon Web Services (AWS). You’ll also learn about security and governance considerations, advanced ML engineering techniques, and how to apply bias detection, explainability, and privacy in ML model development. And finally, you'll get acquainted with AWS AI services and their applications in real-world use cases.By the end of this book, you’ll be able to design and build an ML platform to support common use cases and architecture patterns like a true professional.