Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, et cetera) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts.

Wireless sensor networks. --- Signal processing. --- Machine learning. --- Réseaux de capteurs sans fil --- Traitement du signal --- Apprentissage automatique --- Wireless sensor networks --- Réseaux de capteurs sans fil

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, et cetera) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts.

Wireless sensor networks. --- WSNs (Sensor networks) --- Computer networks --- Low voltage systems --- Sensor networks --- Wireless communication systems --- Context-aware computing

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Take your Python skills to the next level to develop scalable, real-world applications for local as well as cloud deployment Key Features All code examples have been tested with Python 3.7 and Python 3.8 and are expected to work with any future 3.x release Learn how to build modular and object-oriented applications in Python Discover how to use advanced Python techniques for the cloud and clusters Book Description Python is a multipurpose language that can be used for multiple use cases. Python for Geeks will teach you how to advance in your career with the help of expert tips and tricks. You'll start by exploring the different ways of using Python optimally, both from the design and implementation point of view. Next, you'll understand the life cycle of a large-scale Python project. As you advance, you'll focus on different ways of creating an elegant design by modularizing a Python project and learn best practices and design patterns for using Python. You'll also discover how to scale out Python beyond a single thread and how to implement multiprocessing and multithreading in Python. In addition to this, you'll understand how you can not only use Python to deploy on a single machine but also use clusters in private as well as in public cloud computing environments. You'll then explore data processing techniques, focus on reusable, scalable data pipelines, and learn how to use these advanced techniques for network automation, serverless functions, and machine learning. Finally, you'll focus on strategizing web development design using the techniques and best practices covered in the book. By the end of this Python book, you'll be able to do some serious Python programming for large-scale complex projects. What you will learn Understand how to design and manage complex Python projects Strategize test-driven development (TDD) in Python Explore multithreading and multiprogramming in Python Use Python for data processing with Apache Spark and Google Cloud Platform (GCP) Deploy serverless programs on public clouds such as GCP Use Python to build web applications and application programming interfaces Apply Python for network automation and serverless functions Get to grips with Python for data analysis and machine learning Who this book is for This book is for intermediate-level Python developers in any field who are looking to build their skills to develop and manage large-scale complex projects. Developers who want to create reusable modules and...

Programming --- Python (Computer program language) --- Scripting languages (Computer science)

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Get to grips with the most common as well as complex Linux networking configurations, tools, and services to enhance your professional skillsKey Features* Learn how to solve critical networking problems using real-world examples* Configure common networking services step by step in an enterprise environment* Discover how to build infrastructure with an eye toward defense against common attacksBook DescriptionAs Linux continues to gain prominence, there has been a rise in network services being deployed on Linux for cost and flexibility reasons. If you are a networking professional or an infrastructure engineer involved with networks, extensive knowledge of Linux networking is a must.This book will guide you in building a strong foundation of Linux networking concepts. The book begins by covering various major distributions, how to pick the right distro, and basic Linux network configurations. You'll then move on to Linux network diagnostics, setting up a Linux firewall, and using Linux as a host for network services. You'll discover a wide range of network services, why they're important, and how to configure them in an enterprise environment. Finally, as you work with the example builds in this Linux book, you'll learn to configure various services to defend against common attacks. As you advance to the final chapters, you'll be well on your way towards building the underpinnings for an all-Linux datacenter.By the end of this book, you'll be able to not only configure common Linux network services confidently, but also use tried-and-tested methodologies for future Linux installations.What you will learn* Use Linux as a troubleshooting and diagnostics platform* Explore Linux-based network services* Configure a Linux firewall and set it up for network services* Deploy and configure Domain Name System (DNS) and Dynamic Host Configuration Protocol (DHCP) services securely* Configure Linux for load balancing, authentication, and authorization services* Use Linux as a logging platform for network monitoring* Deploy and configure Intrusion Prevention Services (IPS)* Set up Honeypot solutions to detect and foil attacksWho this book is forThis book is for IT and Windows professionals and admins looking for guidance in managing Linux-based networks. Basic knowledge of networking is necessary to get started with this book.

Mathematics --- Operating systems (Computers) --- Linux.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Perform more advanced analysis and manipulation of your data beyond what Power BI can do to unlock valuable insights using Python and R Key Features Get the most out of Python and R with Power BI by implementing non-trivial code Leverage the toolset of Python and R chunks to inject scripts into your Power BI dashboards Implement new techniques for ingesting, enriching, and visualizing data with Python and R in Power BI Book Description Python and R allow you to extend Power BI capabilities to simplify ingestion and transformation activities, enhance dashboards, and highlight insights. With this book, you'll be able to make your artifacts far more interesting and rich in insights using analytical languages. You'll start by learning how to configure your Power BI environment to use your Python and R scripts. The book then explores data ingestion and data transformation extensions, and advances to focus on data augmentation and data visualization. You'll understand how to import data from external sources and transform them using complex algorithms. The book helps you implement personal data de-identification methods such as pseudonymization, anonymization, and masking in Power BI. You'll be able to call external APIs to enrich your data much more quickly using Python programming and R programming. Later, you'll learn advanced Python and R techniques to perform in-depth analysis and extract valuable information using statistics and machine learning. You'll also understand the main statistical features of datasets by plotting multiple visual graphs in the process of creating a machine learning model. By the end of this book, you'll be able to enrich your Power BI data models and visualizations using complex algorithms in Python and R. What you will learn Discover best practices for using Python and R in Power BI products Use Python and R to perform complex data manipulations in Power BI Apply data anonymization and data pseudonymization in Power BI Log data and load large datasets in Power BI using Python and R Enrich your Power BI dashboards using external APIs and machine learning models Extract insights from your data using linear optimization and other algorithms Handle outliers and missing values for multivariate and time-series data Create any visualization, as complex as you want, using R scripts Who this book is for This book is for business analysts, business intelligence professionals, and data scientists who already use Microsoft Power ...

Information visualization --- Visual analytics --- Data mining --- Business intelligence --- R (Computer program language) --- Python (Computer program language) --- Computer programs. --- Data processing.