Beginning LoRa Radio Networks with Arduino
Create your own LoRa wireless projects for non-industrial use and gain a strong basic understanding of the LoRa technology, LoRa WAN, and LPWAN.
You'll start by building your first LoRa wireless channel and then move on to various interesting projects such as setting up networks with a LoRa gateway, communicating with IoT servers using RESTful API and MQTT protocol, and real-time GPS tracking.
With LoRa wireless and LoRaWAN, you can build a wide array of applications in the area of smart agriculture, smart cities, smart environment, smart healthcare, smart homes and buildings, smart industrial control, smart metering, smart supply chain and logistics. Beginning LoRa Radio Networks with Arduino provides a practical introduction and uses affordable and easy to obtain hardware to build projects with the Arduino development environment.
Understand the hardware need to build LoRaWAN; Use the Arduino development environment to write code; Connect to Arduino hardware and upload progr ...
Learn Keras for Deep Neural Networks
Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras.
The overall book comprises three sections with two chapters in each section. The first section prepares you with all the necessary basics to get started in deep learning. Chapter 1 introduces you to the world of deep learning and its difference from machine learning, the choices of frameworks for deep learning, and the Keras ecosystem. You will cover a real-life business problem that can be solved by supervised learning algorithms with deep neural networks. You'll tackle one use case for regression and another for classification leveraging popular Kaggle datasets.
Later, you will see an interesting and challenging part of deep learning: hyperparameter tuning; helping you furthe ...
Deep Learning with PyTorch Quick Start Guide
PyTorch is extremely powerful and yet easy to learn. It provides advanced features, such as supporting multiprocessor, distributed, and parallel computation. This book is an excellent entry point for those wanting to explore deep learning with PyTorch to harness its power.
This book will introduce you to the PyTorch deep learning library and teach you how to train deep learning models without any hassle. We will set up the deep learning environment using PyTorch, and then train and deploy different types of deep learning models, such as CNN, RNN, and autoencoders.
You will learn how to optimize models by tuning hyperparameters and how to use PyTorch in multiprocessor and distributed environments. We will discuss long short-term memory network (LSTMs) and build a language model to predict text.
By the end of this book, you will be familiar with PyTorch's capabilities and be able to utilize the library to train your neural networks with relative ease. ...
CompTIA Network+ Certification Guide
CompTIA certified professionals have always had the upper hand in the information technology industry. This book will be your ideal guide to efficiently passing and achieving this certification. Learn from industry experts and implement their practices to resolve complex IT issues.
This book revolves around networking concepts where readers will learn topics like network architecture, security, network monitoring, and troubleshooting. This book will not only prepare the readers conceptually but will also help them pass the N10-007 exam. This guide will also provide practice exercise after every chapter where readers can ensure their concepts are clear.
By the end of this book, readers will leverage this guide and the included practice questions to boost their confidence in appearing for the actual certificate. ...
pfSense 2.x Cookbook, 2nd Edition
pfSense is an open source distribution of the FreeBSD-based firewall that provides a platform for ﬂexible and powerful routing and firewalling. The versatility of pfSense presents us with a wide array of configuration options, which makes determining requirements a little more difficult and a lot more important compared to other offerings.
pfSense 2.x Cookbook, 2nd Edition starts by providing you with an understanding of how to complete the basic steps needed to render a pfSense firewall operational. It starts by showing you how to set up different forms of NAT entries and firewall rules and use aliases and scheduling in firewall rules. Moving on, you will learn how to implement a captive portal set up in different ways (no authentication, user manager authentication, and RADIUS authentication), as well as NTP and SNMP configuration. You will then learn how to set up a VPN tunnel with pfSense. The book then focuses on setting up traffic shaping with pfSense, using either the built ...
As you make your way through the chapters, you'll learn how to build an API server to interact with your blockchain and how to host your blockchain on a decentralized network. You'll also build a consensus algorithm and use it to verify data and keep the entire blockchain network synchronized. In the concluding chapters, you'll finish building your blockchain prototype and gain a thorough understanding of why blockchain technology is so secure and valuable.
By the end of this book, you'll understand how d ...
Linux Basics for Hackers
If you're getting started along the exciting path of hacking, cybersecurity, and pentesting, Linux Basics for Hackers is an excellent first step. Using Kali Linux, an advanced penetration testing distribution of Linux, you'll learn the basics of using the Linux operating system and acquire the tools and techniques you'll need to take control of a Linux environment.
First, you'll learn how to install Kali on a virtual machine and get an introduction to basic Linux concepts. Next, you'll tackle broader Linux topics like manipulating text, controlling file and directory permissions, and managing user environment variables. You'll then focus in on foundational hacking concepts like security and anonymity and learn scripting skills with bash and Python. Practical tutorials and exercises throughout will reinforce and test your skills as you learn how to: Cover your tracks by changing your network information and manipulating the rsyslog logging utility; Write a tool to scan for ...
Recurrent Neural Networks with Python Quick Start Guide
Developers struggle to find an easy-to-follow learning resource for implementing Recurrent Neural Network (RNN) models. RNNs are the state-of-the-art model in deep learning for dealing with sequential data. From language translation to generating captions for an image, RNNs are used to continuously improve results. This book will teach you the fundamentals of RNNs, with example applications in Python and the TensorFlow library. The examples are accompanied by the right combination of theoretical knowledge and real-world implementations of concepts to build a solid foundation of neural network modeling.
Your journey starts with the simplest RNN model, where you can grasp the fundamentals. The book then builds on this by proposing more advanced and complex algorithms. We use them to explain how a typical state-of-the-art RNN model works. From generating text to building a language translator, we show how some of today's most powerful AI applications work under the hood. ...
Python Deep Learning Projects
Deep learning has been gradually revolutionizing every field of artificial intelligence, making application development easier.
Python Deep Learning Projects imparts all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each of these projects is unique, helping you progressively master the subject. You'll learn how to implement a text classifier system using a recurrent neural network (RNN) model and optimize it to understand the shortcomings you might experience while implementing a simple deep learning system.
Similarly, you'll discover how to develop various projects, including word vector representation, open domain question answering, and building chatbots using seq-to-seq models and language modeling. In addition to this, you'll cover advanced concepts, such as regularization, gradient clipping, gradient normalization, and bidirectional RNNs, through a series of engaging projects.
By the ...
CCNA Routing and Switching 200-125 Certification Guide
Cisco Certified Network Associate (CCNA) Routing and Switching is one of the most important qualifications for keeping your networking skills up to date. CCNA Routing and Switching 200-125 Certification Guide covers topics included in the latest CCNA exam, along with review and practice questions. This guide introduces you to the structure of IPv4 and IPv6 addresses and examines in detail the creation of IP networks and sub-networks and how to assign addresses in the network.
You will then move on to understanding how to configure, verify, and troubleshoot layer 2 and layer 3 protocols.
In addition to this, you will discover the functionality, configuration, and troubleshooting of DHCPv4. Combined with router and router simulation practice, this certification guide will help you cover everything you need to know in order to pass the CCNA Routing and Switching 200-125 exam.
By the end of this book, you will explore security best practices, as well as get familiar with th ...
Keras Deep Learning Cookbook
Keras has quickly emerged as a popular deep learning library. Written in Python, it allows you to train convolutional as well as recurrent neural networks with speed and accuracy.
The Keras Deep Learning Cookbook shows you how to tackle different problems encountered while training efficient deep learning models, with the help of the popular Keras library. Starting with installing and setting up Keras, the book demonstrates how you can perform deep learning with Keras in the TensorFlow. From loading data to fitting and evaluating your model for optimal performance, you will work through a step-by-step process to tackle every possible problem faced while training deep models. You will implement convolutional and recurrent neural networks, adversarial networks, and more with the help of this handy guide. In addition to this, you will learn how to train these models for real-world image and language processing tasks.
By the end of this book, you will have a practical, hands-on under ...