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Podcasts
It’s becoming more and more apparent that security is a critical aspect of IT infrastructure. A data breach is a major security incident, usually carried out by just hacking a simple network line. Increasing your network’s security helps step up your defenses against cyber attacks. Meanwhile, Python is being used for increasingly advanced tasks, with the latest update introducing many new packages. This book focuses on leveraging these updated packages to build a secure network with the help of Python scripting. This book covers topics from building a network to the different procedures you need to follow to secure it. You’ll first be introduced to different packages and libraries, before moving on to different ways to build a network with the help of Python scripting. Later, you will learn how to check a network’s vulnerability using Python security scripting, and understand how to check vulnerabilities in your network. As you progress through the chapters, you will also learn how to achieve endpoint protection by leveraging Python packages along with writing forensic scripts. By the end of this book, you will be able to get the most out of the Python language to build secure and robust networks that are resilient to attacks.
TensorFlow is one of the most popular machine learning frameworks in Python. With this book, you will improve your knowledge of some of the latest TensorFlow features and will be able to perform supervised and unsupervised machine learning and also train neural networks.After giving you an overview of what's new in TensorFlow 2.0 Alpha, the book moves on to setting up your machine learning environment using the TensorFlow library. You will perform popular supervised machine learning tasks using techniques such as linear regression, logistic regression, and clustering. You will get familiar with unsupervised learning for autoencoder applications. The book will also show you how to train effective neural networks using straightforward examples in a variety of different domains.By the end of the book, you will have been exposed to a large variety of machine learning and neural network TensorFlow techniques.
Machine learning has had a huge impact on academia and industry by turning data into actionable information. Scala has seen a steady rise in adoption over the past few years, especially in the fields of data science and analytics. This book is for data scientists, data engineers, and deep learning enthusiasts who have a background in complex numerical computing and want to know more hands-on machine learning application development.If you're well versed in machine learning concepts and want to expand your knowledge by delving into the practical implementation of these concepts using the power of Scala, then this book is what you need! Through 11 end-to-end projects, you will be acquainted with popular machine learning libraries such as Spark ML, H2O, DeepLearning4j, and MXNet.At the end, you will be able to use numerical computing and functional programming to carry out complex numerical tasks to develop, build, and deploy research or commercial projects in a production-ready environment.
For developers who prefer a more simplistic approach to coding, Kotlin has emerged as a valuable solution for effective software development. The Kotlin standard library provides vital tools that make day-to-day Kotlin programming easier. This library features core attributes of the language, such as algorithmic problems, design patterns, data processing, and working with files and data streams.With a recipe-based approach, this book features coding solutions that you can readily execute. Through the book, you’ll encounter a variety of interesting topics related to data processing, I/O operations, and collections transformation. You’ll get started by exploring the most effective design patterns in Kotlin and understand how coroutines add new features to JavaScript. As you progress, you'll learn how to implement clean, reusable functions and scalable interfaces containing default implementations. Toward the concluding chapters, you’ll discover recipes on functional programming concepts, such as lambdas, monads, functors, and Kotlin scoping functions, which will help you tackle a range of real-life coding problems. By the end of this book, you'll be equipped with the expertise you need to address a range of challenges that Kotlin developers face by implementing easy-to-follow solutions.
Since their introduction to Unity, shaders have been seen as notoriously difficult to understand and implement in games. Complex mathematics has always stood in the way of creating your own shaders and attaining the level of realism you crave.Unity 2018 Shaders and Effects Cookbook changes that by giving you a recipe-based guide to creating shaders using Unity. It will show you everything you need to know about vectors, how lighting is constructed with them, and how textures are used to create complex effects without the heavy math.This book starts by teaching you how to use shaders without writing code with the post-processing stack. Then, you’ll learn how to write shaders from scratch, build up essential lighting, and finish by creating stunning screen effects just like those in high-quality 3D and mobile games. You'll discover techniques, such as normal mapping, image-based lighting, and animating your models inside a shader. We'll explore how to use physically based rendering to treat light the way it behaves in the real world. At the end, we’ll even look at Unity 2018’s new Shader Graph system.With this book, what seems like a dark art today will be second nature by tomorrow.
Shivakumar Gopalakrishnan, Gunther Lenz
Microsoft is now one of the most significant contributors to Kubernetes open source projects. Kubernetes helps to create, configure, and manage a cluster of virtual machines that are preconfigured to run containerized applications.This book will be your guide to performing successful container orchestration and deployment of Kubernetes clusters on Azure. You will get started by learning how to deploy and manage highly scalable applications, along with understanding how to set up a production-ready Kubernetes cluster on Azure. As you advance, you will learn how to reduce the complexity and operational overheads of managing a Kubernetes cluster on Azure.By the end of this book, you will not only be capable of deploying and managing Kubernetes clusters on Azure with ease, but also have the knowledge of best practices for working with advanced AKS concepts for complex systems.
Fundamentals of Linux. Explore the essentials of the Linux command line
Linux is a Unix-like operating system assembled under the model of free and open source software development and distribution. Fundamentals of Linux will help you learn all the essentials of the Linux command line required to get you started. The book will start by teaching you how to work with virtualization software and install CentOS 7 Linux as a VM. Then, you will get to grips with the workings of various command line operations, such as cursor movement, commands, options, and arguments. As you make your way through the chapters, the book will not only focus on the most essential Linux commands but also give an introduction to Bash shell scripting. Finally, you will explore advanced topics, such as networking and troubleshooting your system, and you will get familiar with the advanced file permissions: ACL, setuid, and setgid. Fundamentals of Linux includes real-world tasks, use cases, and problems that, as a system administrator, you might encounter in your day-to-day activities.
Apache Mesos Cookbook. Efficiently handle and manage tasks in a distributed environment
David Blomquist, Tomasz Janiszewski
Apache Mesos is open source cluster sharing and management software. Deploying and managing scalable applications in large-scale clustered environments can be difficult, but Apache Mesos makes it easier with efficient resource isolation and sharing across application frameworks.The goal of this book is to guide you through the practical implementation of the Mesos core along with a number of Mesos supported frameworks. You will begin by installing Mesos and then learn how to configure clusters and maintain them. You will also see how to deploy a cluster in a production environment with high availability using Zookeeper.Next, you will get to grips with using Mesos, Marathon, and Docker to build and deploy a PaaS. You will see how to schedule jobs with Chronos. We’ll demonstrate how to integrate Mesos with big data frameworks such as Spark, Hadoop, and Storm. Practical solutions backed with clear examples will also show you how to deploy elastic big data jobs. You will find out how to deploy a scalable continuous integration and delivery system on Mesos with Jenkins. Finally, you will configure and deploy a highly scalable distributed search engine with ElasticSearch.Throughout the course of this book, you will get to know tips and tricks along with best practices to follow when working with Mesos.