A journey toward containerized applications in production with a cloud-portable, secure, robust and highly available Docker Enterprise platform. Key Features * Get an insider’s view into the container movement and Docker Enterprise * Manage the transformation associated with enterprise container adoption * Walk through the enterprise container adoption journey Book Description While known mostly as the open source engine behind tens of millions of server nodes, Docker also offers commercially supported enterprise tooling known as the Docker Enterprise. This platform leverages the deep roots from Docker Engine - Community (formerly Docker CE) and Kubernetes, but adds support and tooling to efficiently operate a secure container platform at scale. With hundreds of enterprises on board, best practices and adoption patterns are emerging rapidly. These learning points can be used to inform adopters and help manage the enterprise transformation associated with enterprise container adoption. This book starts by explaining the case for Docker Enterprise, as well as its structure and reference architecture. From there, we progress through the PoC,pilot and production stages as a working model for adoption, evolving the platform’s design and configuration for each stage and using detailed application examples along the way to clarify and demonstrate important concepts.The book concludes with Docker’s impact on other emerging software technologies, such as Blockchain and Serverless computing. By the end of this book, you’ll have a better understanding of what it takes to get your enterprise up and running with Docker Enterprise and beyond. What you will learn * Understand why containers are important to an enterprise * Understand the features and components of Docker Enterprise 2 * Find out about the PoC, pilot, and production adoption phases * Get to know the best practices for installing and operating Docker Enterprise * Understand what is important for a Docker Enterprise in production * Run Kubernetes on Docker Enterprise Who this book is for This book is for Software Architects, DevOps Engineers, Tech Ops, Docker professionals, or any IT professional working with Docker and containers who wants to move containerized workloads to production. This book discusses the enterprise adoption of Docker and Kubernetes,therefore a basic understanding of Docker concepts will be helpful.

Choose the smarter way to learn about containerizing your applications and running them in production. Key Features * Deploy and manage highly scalable, containerized applications with Kubernetes * Build high-availability Kubernetes clusters * Secure your applications via encapsulation, networks, and secrets Book Description Kubernetes is an open source orchestration platform for managing containers in a cluster environment. This Learning Path introduces you to the world of containerization, in addition to providing you with an overview of Docker fundamentals. As you progress, you will be able to understand how Kubernetes works with containers. Starting with creating Kubernetes clusters and running applications with proper authentication and authorization, you'll learn how to create high-availability Kubernetes clusters on Amazon Web Services (AWS), and also learn how to use kubeconfig to manage different clusters. Whether it is learning about Docker containers and Docker Compose, or building a continuous delivery pipeline for your application, this Learning Path will equip you with all the right tools and techniques to get started with containerization. By the end of this Learning Path, you will have gained hands-on experience of working with Docker containers and orchestrators, including SwarmKit and Kubernetes. This Learning Path includes content from the following Packt products: * Kubernetes Cookbook - Second Edition by Hideto Saito, Hui-Chuan Chloe Lee, and Ke-Jou Carol Hsu * Learn Docker - Fundamentals of Docker 18.x by Gabriel N. Schenker What you will learn * Build your own container cluster * Run a highly distributed application with Docker Swarm or Kubernetes * Update or rollback a distributed application with zero downtime * Containerize your traditional or microservice-based application * Build a continuous delivery pipeline for your application * Track metrics and logs for every container in your cluster * Implement container orchestration to streamline deploying and managing applications Who this book is for This beginner-level Learning Path is designed for system administrators, operations engineers, DevOps engineers, and developers who want to get started with Docker and Kubernetes. Although no prior experience with Docker is required, basic knowledge of Kubernetes and containers will be helpful.

A practical guide to testing your infrastructure security with Kali Linux, the preferred choice of pentesters and hackers Key Features * Employ advanced pentesting techniques with Kali Linux to build highly secured systems * Discover various stealth techniques to remain undetected and defeat modern infrastructures * Explore red teaming techniques to exploit secured environment Book Description This book takes you, as a tester or security practitioner, through the reconnaissance, vulnerability assessment, exploitation, privilege escalation, and post-exploitation activities used by pentesters. To start with, you'll use a laboratory environment to validate tools and techniques, along with an application that supports a collaborative approach for pentesting. You'll then progress to passive reconnaissance with open source intelligence and active reconnaissance of the external and internal infrastructure. You'll also focus on how to select, use, customize, and interpret the results from different vulnerability scanners, followed by examining specific routes to the target, which include bypassing physical security and the exfiltration of data using a variety of techniques. You'll discover concepts such as social engineering, attacking wireless networks, web services, and embedded devices. Once you are confident with these topics, you'll learn the practical aspects of attacking user client systems by backdooring with fileless techniques, followed by focusing on the most vulnerable part of the network – directly attacking the end user. By the end of this book, you'll have explored approaches for carrying out advanced pentesting in tightly secured environments, understood pentesting and hacking techniques employed on embedded peripheral devices. What you will learn * Configure the most effective Kali Linux tools to test infrastructure security * Employ stealth to avoid detection in the infrastructure being tested * Recognize when stealth attacks are being used against your infrastructure * Exploit networks and data systems using wired and wireless networks as well as web services * Identify and download valuable data from target systems * Maintain access to compromised systems * Use social engineering to compromise the weakest part of the network - the end users Who this book is for This third edition of Mastering Kali Linux for Advanced Penetration Testing is for you if you are a security analyst, pentester, ethical hacker, IT professional, or security consultant wanting to maximize the success of your infrastructure testing using some of the advanced features of Kali Linux. Prior exposure of penetration testing and ethical hacking basics will be helpful in making the most out of this book.

Gather detailed statistics and deploy impressive business solutions with Zabbix 4.0 Key Features *Experience the full impact of Zabbix 4.0, a useful and increasingly popular tool *Enhance your network’s performance and manage hosts and systems *A step-by-step guide to smarter network monitoring Book Description Zabbix 4 Network Monitoring is the perfect starting point for monitoring the performance of your network devices and applications with Zabbix. Even if you’ve never used a monitoring solution before, this book will get you up and running quickly. You’ll learn to monitor more sophisticated operations with ease and soon feel in complete control of your network, ready to meet any challenges you might face. Starting with the installation, you will discover the new features in Zabbix 4.0. You will then get to grips with native Zabbix agents and Simple Network Management Protocol (SNMP) devices. You will also explore Zabbix's integrated functionality for monitoring Java application servers and VMware. This book also covers notifications, permission management, system maintenance, and troubleshooting, so you can be confident that every potential challenge and task is under your control. If you're working with larger environments, you'll also be able to find out more about distributed data collection using Zabbix proxies. Once you're confident and ready to put these concepts into practice, you will understand how to optimize and improve performance. Troubleshooting network issues is vital for anyone working with Zabbix, so the book also helps you work through any technical snags and glitches you might face. By the end of this book, you will have learned more advanced techniques to fine-tune your system and make sure it is in a healthy state. What you will learn *Install Zabbix server and an agent from source *Manage hosts, users, and permissions while acting upon monitored conditions *Visualize data with the help of ad hoc graphs, custom graphs, and maps *Simplify complex configurations and learn to automate them *Monitor everything from web pages to IPMI devices and Java applications to VMware stats *Configure Zabbix to send alerts including problem severity and time periods *Troubleshoot any network issue Who this book is for If you're new to Zabbix look no further than this book. Zabbix 4 Network Monitoring is for system and network administrators who are looking to put their knowledge to work with Zabbix 4.0.

Build clever, collaborative, and powerful automation systems with the Raspberry Pi and Python. Key Features * Create your own Pi-Rover or Pi-Hexipod robots * Develop practical applications in Python using Raspberry Pi * Build your own Jarvis, a highly advanced computerized AI Book Description This Learning Path takes you on a journey in the world of robotics and teaches you all that you can achieve with Raspberry Pi and Python. It teaches you to harness the power of Python with the Raspberry Pi 3 and the Raspberry Pi zero to build superlative automation systems that can transform your business. You will learn to create text classifiers, predict sentiment in words, and develop applications with the Tkinter library. Things will get more interesting when you build a human face detection and recognition system and a home automation system in Python, where different appliances are controlled using the Raspberry Pi. With such diverse robotics projects, you'll grasp the basics of robotics and its functions, and understand the integration of robotics with the IoT environment. By the end of this Learning Path, you will have covered everything from configuring a robotic controller, to creating a self-driven robotic vehicle using Python. * Raspberry Pi 3 Cookbook for Python Programmers - Third Edition by Tim Cox, Dr. Steven Lawrence Fernandes * Python Programming with Raspberry Pi by Sai Yamanoor, Srihari Yamanoor * Python Robotics Projects by Prof. Diwakar Vaish What you will learn * Build text classifiers and predict sentiment in words with the Tkinter library * Develop human face detection and recognition systems * Create a neural network module for optical character recognition * Build a mobile robot using the Raspberry Pi as a controller * Understand how to interface sensors, actuators, and LED displays work * Apply machine learning techniques to your models * Interface your robots with Bluetooth Who this book is for This Learning Path is specially designed for Python developers who want to take their skills to the next level by creating robots that can enhance people’s lives. Familiarity with Python and electronics will aid understanding the concepts in this Learning Path.

Build efficient data flow and machine learning programs with this flexible, multi-functional open-source cluster-computing framework Key Features *Master the art of real-time big data processing and machine learning *Explore a wide range of use-cases to analyze large data *Discover ways to optimize your work by using many features of Spark 2.x and Scala Book Description Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform. You will work with the different modules in Apache Spark, such as interactive querying with Spark SQL, using DataFrames and datasets, implementing streaming analytics with Spark Streaming, and applying machine learning and deep learning techniques on Spark using MLlib and various external tools. By the end of this elaborately designed Learning Path, you will have all the knowledge you need to master Apache Spark, and build your own big data processing and analytics pipeline quickly and without any hassle. This Learning Path includes content from the following Packt products: *Mastering Apache Spark 2.x by Romeo Kienzler *Scala and Spark for Big Data Analytics by Md. Rezaul Karim, Sridhar Alla *Apache Spark 2.x Machine Learning Cookbook by Siamak Amirghodsi, Meenakshi Rajendran, Broderick Hall, Shuen MeiCookbook What you will learn *Get to grips with all the features of Apache Spark 2.x *Perform highly optimized real-time big data processing *Use ML and DL techniques with Spark MLlib and third-party tools *Analyze structured and unstructured data using SparkSQL and GraphX *Understand tuning, debugging, and monitoring of big data applications *Build scalable and fault-tolerant streaming applications *Develop scalable recommendation engines Who this book is for If you are an intermediate-level Spark developer looking to master the advanced capabilities and use-cases of Apache Spark 2.x, this Learning Path is ideal for you. Big data professionals who want to learn how to integrate and use the features of Apache Spark and build a strong big data pipeline will also find this Learning Path useful. To grasp the concepts explained in this Learning Path, you must know the fundamentals of Apache Spark and Scala.

Build cost-effective and robust cloud solutions with Google Cloud Platform (GCP) using these simple and practical recipes Key Features * Explore the various service offerings of the GCP * Host a Python application on Google Compute Engine * Securely maintain application states with Cloud Storage, Datastore, and Bigtable Book Description GCP is a cloud computing platform with a wide range of products and services that enable you to build and deploy cloud-hosted applications. This Learning Path will guide you in using GCP and designing, deploying, and managing applications on Google Cloud. You will get started by learning how to use App Engine to access Google's scalable hosting and build software that runs on this framework. With the help of Google Compute Engine, you’ll be able to host your workload on virtual machine instances. The later chapters will help you to explore ways to implement authentication and security, Cloud APIs, and command-line and deployment management. As you hone your skills, you’ll understand how to integrate your new applications with various data solutions on GCP, including Cloud SQL, Bigtable, and Cloud Storage. Following this, the book will teach you how to streamline your workflow with tools, including Source Repositories, Container Builder, and Stackdriver. You'll also understand how to deploy and debug services with IntelliJ, implement continuous delivery pipelines, and configure robust monitoring and alerts for your production systems. By the end of this Learning Path, you'll be well versed with GCP’s development tools and be able to develop, deploy, and manage highly scalable and reliable applications. This Learning Path includes content from the following Packt products: * Google Cloud Platform for Developers Ted Hunter and Steven Porter * Google Cloud Platform Cookbook by Legorie Rajan PS What you will learn * Host an application using Google Cloud Functions * Migrate a MySQL database to Cloud Spanner * Configure a network for a highly available application on GCP * Learn simple image processing using Storage and Cloud Functions * Automate security checks using Policy Scanner * Deploy and run services on App Engine and Container Engine * Minimize downtime and mitigate issues with Stackdriver Monitoring and Debugger * Integrate with big data solutions, including BigQuery, Dataflow, and Pub/Sub Who this book is for This Learning Path is for IT professionals, engineers, and developers who want to implement Google Cloud in their organizations. Administrators and architects planning to make their organization more efficient with Google Cloud will also find this Learning Path useful. Basic understanding of GCP and its services is a must.

Work through recipes to unlock the full potential of the next generation graphics API―Vulkan About This Book ?This book explores a wide range of modern graphics programming techniques and GPU compute methods to make the best use of the Vulkan API ?Learn techniques that can be applied to a wide range of platforms desktop, smartphones, and embedded devices Who This Book Is For This book is ideal for developers who know C/C++ languages, have some basic familiarity with graphics programming, and now want to take advantage of the new Vulkan API in the process of building next generation computer graphics. Some basic familiarity of Vulkan would be useful to follow the recipes. OpenGL developers who want to take advantage of the Vulkan API will also find this book useful. What You Will Learn?Work with Swapchain to present images on screen ?Create, submit, and synchronize operations processed by the hardware ?Create buffers and images, manage their memory, and upload data to them from CPU ?Explore de*or sets and set up an interface between application and shaders ?Organize drawing operations into a set of render passes and subpasses ?Prepare graphics pipelines to draw 3D scenes and compute pipelines to perform mathematical calculations ?Implement geometry projection and tessellation, texturing, lighting, and post-processing techniques ?Write shaders in GLSL and convert them into SPIR-V assemblies ?Find out about and

"Key Features ?Get to the grips with the latest version of Apache Spark ?Utilize Spark's machine learning library to implement predictive analytics ?Leverage Spark's powerful tools to load, analyze, clean, and transform your data Book De*ion Spark ML is the machine learning module of Spark. It uses in-memory RDDs to process machine learning models faster for clustering, classification, and regression. This book will teach you about popular machine learning algorithms and their implementation. You will learn how various machine learning concepts are implemented in the context of Spark ML. You will start by installing Spark in a single and multinode cluster. Next you'll see how to execute Scala and Python based programs for Spark ML. Then we will take a few datasets and go deeper into clustering, classification, and regression. Toward the end, we will also cover text processing using Spark ML. Once you have learned the concepts, they can be applied to implement algorithms in either green-field implementations or to migrate existing systems to this new platform. You can migrate from Mahout or Scikit to use Spark ML. What you will learn ?Get hands-on with the latest version of Spark ML ?Create your first Spark program with Scala and Python ?Set up and configure a development environment for Spark on your own computer, as well as on Amazon EC2 ?Access public machine learning datasets and use Spark to load, process, clean, and transform data ?Use Spark's machine learning library to implement programs by utilizing well-known machine learning models ?Deal with large-scale text data, including feature extraction and using text data as input to your machine learning models ?Write Spark functions to evaluate the performance of your machine learning models "

Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of this comprehensive TensorFlow guide About This Book ?Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow ?Explore deep neural networks and layers of data abstraction with the help of this comprehensive guide ?Real-world contextualization through some deep learning problems concerning research and application Who This Book Is For The book is intended for a general audience of people interested in machine learning and machine intelligence. A rudimentary level of programming in one language is assumed, as is a basic familiarity with computer science techniques and technologies, including a basic awareness of computer hardware and algorithms. Some competence in mathematics is needed to the level of elementary linear algebra and calculus. What You Will Learn ?Learn about machine learning landscapes along with the historical development and progress of deep learning ?Learn about deep machine intelligence and GPU computing with the latest TensorFlow 1.x ?Access public datasets and utilize them using TensorFlow to load, process, and transform data ?Use TensorFlow on real-world datasets, including images, text, and more ?Learn how to evaluate the performance of your deep learning models ?Using deep learning for scalable object detection and mobile computing ?Train machines quickly to learn from data by exploring reinforcement learning techniques ?Explore active areas of deep learning research and applications

Do you want to make sense of your data? Do you want to create interactive charts, data trees, info-graphics, geospatial charts, and maps efficiently? This book is your ideal choice to master interactive data visualization with D3.js V4. The book includes a number of extensive examples that to help you hone your skills with data visualization. Throughout nine chapters these examples will help you acquire a clear practical understanding of the various techniques, tools and functionality provided by D3.js. You will first setup your D3.JS development environment and learn the basic patterns needed to visualize your data. After that you will learn techniques to optimize different processes such as working with selections; animating data transitions; creating graps and charts, integrating external resources (static as well as streaming); visualizing information on maps; working with colors and scales; utilizing the different D3.js APIs; and much more. The book will also guide you through creating custom graphs and visualizations, and show you how to go from the raw data to beautiful visualizations. The extensive examples will include working with complex and realtime data streams, such as seismic data, geospatial data, scientific data, and more. Towards the end of the book, you will learn to add more functionality on top of D3.js by using it with other external libraries and integrating it with Ecma* 6 and Type*

Writing concurrent and parallel programming applications is an integral skill for any Java programmer. Java 9 comes with a host of fantastic features, including significant performance improvements and new APIs. This book will take you through all the new APIs, showing you how to build parallel and multi-threaded applications. The book covers all the elements of the Java Concurrency API, with essential recipes that will help you take advantage of the exciting new capabilities. You will learn how to use parallel and reactive streams to process massive data sets. Next, you will move on to create streams and use all their intermediate and terminal operations to process big collections of data in a parallel and functional way. Further, you ll discover a whole range of recipes for almost everything, such as thread management, synchronization, executors, parallel and reactive streams, and many more. At the end of the book, you will learn how to obtain information about the status of some of the most useful components of the Java Concurrency API and how to test concurrent applications using different tools. What you will learn ?Find out to manage the basic components of the Java Concurrency API ?Use synchronization mechanisms to avoid data race conditions and other problems of concurrent applications ?Separate the thread management from the rest of the application with the Executor framework ?Solve problems using a parallelized version of the divide and conquer paradigm with the Fork / Join framework ?Process massive data sets in an optimized way using streams and reactive streams ?See which data structures we can use in concurrent applications and how to use them ?Practice efficient techniques to test concurrent applications ?Get to know tips and tricks to design concurrent applications

This book starts by introducing you to supervised learning algorithms such as simple linear regression, the classical multilayer perceptron and more sophisticated deep convolutional networks. You will also explore image processing with recognition of hand written digit images, classification of images into different categories, and advanced objects recognition with related image annotations. An example of identification of salient points for face detection is also provided. Next you will be introduced to Recurrent Networks, which are optimized for processing sequence data such as text, audio or time series. Following that, you will learn about unsupervised learning algorithms such as Autoencoders and the very popular Generative Adversarial Networks (GAN). You will also explore non-traditional uses of neural networks as Style Transfer. Finally, you will look at Reinforcement Learning and its application to AI game playing, another popular direction of research and application of neural networks. What you will learn ?Optimize step-by-step functions on a large neural network using the Backpropagation Algorithm ?Fine-tune a neural network to improve the quality of results ?Use deep learning for image and audio processing ?Use Recursive Neural Tensor Networks (RNTNs) to outperform standard word embedding in special cases ?Identify problems

Spatial statistics has the potential to provide insight that is not otherwise available through traditional GIS tools. This book is designed to introduce you to the use of spatial statistics so you can solve complex geographic analysis. The book begins by introducing you to the many spatial statistics tools available in ArcGIS. You will learn how to analyze patterns, map clusters, and model spatial relationships with these tools. Further on, you will explore how to extend the spatial statistics tools currently available in ArcGIS, and use the R programming language to create custom tools in ArcGIS through the ArcGIS Bridge using real-world examples. At the end of the book, you will be presented with two exciting case studies where you will be able to practically apply all your learning to analyze and gain insights into real estate data. What you will learn ?Get to know how to measure geographic distributions ?Perform clustering analysis including hot spot and outlier analysis ?Conduct data conversion tasks using the Utilities toolset ?Understand how to use the tools provided by the Mapping Clusters toolset in the Spatial Statistics Toolbox ?Get to grips with the basics of R for performing spatial statistical programming ?Create custom ArcGIS tools with R and ArcGIS Bridge ?Understand the application of Spatial Statistics tools

Java is the most popular programming language, according to the TIOBE index, and it is a typical choice for running production systems in many companies, both in the startup world and among large enterprises. Not surprisingly, it is also a common choice for creating data science applications: it is fast and has a great set of data processing tools, both built-in and external. What is more, choosing Java for data science allows you to easily integrate solutions with existing software, and bring data science into production with less effort. This book will teach you how to create data science applications with Java. First, we will revise the most important things when starting a data science application, and then brush up the basics of Java and machine learning before diving into more advanced topics. We start by going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrieval and natural language processing, and deep learning and big data. Finally, we finish the book by talking about the ways to deploy the model and evaluate it in production settings. What you will learn ?Get a solid understanding of the data processing toolbox available in Java ?Explore the data science ecosystem available in Java

Over 60 practical recipes on data exploration and analysis About This Book Clean dirty data, extract accurate information, and explore the relationships between variables Forecast the output of an electric plant and the water flow of American rivers using pandas, NumPy, Statsmodels, and scikit-learn Find and extract the most important features from your dataset using the most efficient Python libraries Who This Book Is For If you are a beginner or intermediate-level professional who is looking to solve your day-to-day, analytical problems with Python, this book is for you. Even with no prior programming and data analytics experience, you will be able to finish each recipe and learn while doing so. What You Will Learn Read, clean, transform, and store your data usng Pandas and OpenRefine Understand your data and explore the relationships between variables using Pandas and D3.js Explore a variety of techniques to classify and cluster outbound marketing campaign calls data of a bank using Pandas, mlpy, NumPy, and Statsmodels Reduce the dimensionality of your dataset and extract the most important features with pandas, NumPy, and mlpy Predict the output of a power plant with regression models and forecast water flow of American rivers with time series methods using pandas, NumPy, Statsmodels, and scikit-learn Explore social interactions and identify fraudulent activities with graph theory concepts using NetworkX and Gephi Scrape Internet web pages using urlib and BeautifulSoup and get to know natural language processing techniques to classify movies ratings using NLTK Study simulation techniques in an example of a gas station with agent-based modeling In Detail Data analysis is the process of systematically applying statistical and logical techniques to describe and illustrate, condense and recap, and evaluate data. Its importance has been most visible in the sector of information and communication technologies. It is an employee asset in almost all economy sectors. This book provides a rich set of independent recipes that dive into the world of data analytics and modeling using a variety of approaches, tools, and algorithms. You will learn the basics of data handling and modeling, and will build your skills gradually toward more advanced topics such as simulations, raw text processing, social interactions analysis, and more. First, you will learn some easy-to-follow practical techniques on how to read, write, clean, reformat, explore, and understand your data—arguably the most time-consuming (and the most important) tasks for any data scientist. In the second section, different independent recipes delve into intermediate topics such as classification, clustering, predicting, and more. With the help of these easy-to-follow recipes, you will also learn techniques that can easily be expanded to solve other real-life problems such as building recommendation engines or predictive models. In the third section, you will explore more advanced topics: from the field of graph theory through natural language processing, discrete choice modeling to simulations. You will also get to expand your knowledge on identifying fraud origin with the help of a graph, scrape Internet websites, and classify movies based on their reviews. By the end of this book, you will be able to efficiently use the vast array of tools that the Python environment has to offer. Style and approach This hands-on recipe guide is divided into three sections that tackle and overcome real-world data modeling problems faced by data analysts/scientist in their everyday work. Each independent recipe is written in an easy-to-follow and step-by-step fashion.

Build effective applications by applying Odoo development best practices About This Book Each recipe stands by itself as much as possible, so that you can jump straight into the topics you prefer The recipes included cover all the major development areas of Odoo and the most important techniques explained through real-life projects From seasoned authors, learn the tricks of becoming a productive developer with the Odoo framework Who This Book Is For If you are a Python developer who wants to learn or consolidate your Odoo development skills, then this book is for you! Some experience with the JavaScript programming language and web development is required to fully benefit from the front-end chapters. What You Will Learn Install and manage Odoo environments and instances Use Models to define your application's data structures Add business logic to your applications Implement automated tests and debug Odoo apps Use back-end views to create a user interface Get to know about the access security model and internationalization features Develop front-end website features Extend the web client with new widgets and features In Detail Odoo is a full-featured open source ERP with a focus on extensibility. The flexibility and sustainability of open source is also a key selling point of Odoo. It is built on a powerful framework for rapid application development, both for back-end applications and front-end websites. The book starts by covering Odoo installation and administration, and provides a gentle introduction to application development. It then dives deep into several of the areas that an experienced developer will need to use. You’ll learn implement business logic, adapt the UI, and extend existing features. Style and Approach These practical and easy-to-follow recipes are presented step-by-step, with dozens of hands-on recipes to boost your Odoo skills. This book can also be used as a reference guide for your daily work.

An example-based practical guide to get you up and running with Unreal Engine 4.X About This Book A unique resource on Unreal with an interactive example based approach that is sure to get you up and running immediately Will feature four unique game projects that increase in complexity which will enable readers to build their game development skills using Unreal Engine 4 and the C++ programming language Will be the most up to date book in the market on Unreal with full coverage of the new features of UE4 Who This Book Is For Unreal Engine 4.X by Example was written for keen developers who wish to learn how to fully utilise Unreal Engine 4 to make awesome and engrossing game titles. Whether you are brand new to game development or a seasoned expert, you will be able to make use of the engine with C++. Experience with both C++ and other game engines is preferred before embarking on the Unreal by Example journey, but with a little external research into the basics of C++ programming, this book can take a complete game development novice to an Unreal Engine Developer! What You Will Learn Use C++ with Unreal Engine to boost the development potential of any Unreal Engine project Vastly improve workflow and content creation with the visual *ing system blueprint Design, test, and implement interesting game worlds using Unreal Engines built-in editor Build a networked, feature-rich first person shooter that you can play with others over LAN Build design-centric game worlds that play to needs of your game ideas Paint your game worlds via the creation and modification of visual shaders called materials Gain knowledge of other game development disciplines through the use of the Animation and Material tool sets Create feature-rich game projects with a sophisticated visual quality and feature set In Detail With Unreal Engine 4 being made free to use, for any keen game developer it is quickly becoming the most popular game engine in today’s development industry. The engine offers a rich feature set that can be customized and built upon through the use of C++. This book will cover how to work with Unreal Engine’s tool set all the way from the basics of the editor and the visual *ing system blueprint to the in-depth low-level creation of content using C++. This book will provide you with the skills you need to create feature-rich, captivating, and refined game titles with Unreal Engine 4. This book will take you through the creation of four unique game projects, designed so that you will be ready to apply the engine’s rich development capabilities. You will learn not only to take advantage of the visual tools of the engine, but also the vast and powerful programming feature set of Unreal Engine 4. Style and approach The best resource that any beginner level game developer can dream of with examples on leveraging the amazing graphics engine, beautiful character animation and game world generations etc. by means of exciting real world game generation.This book would be a very unique resource for any game developer who wants to get up and running with Unreal. The unique example-driven approach will take you through the most basic games towards the more complex ones and will gradually build your skill level.

Take your penetration testing and IT security skills to a whole new level with the secrets of Metasploit About This Book Gain the skills to carry out penetration testing in complex and highly-secured environments Become a master using the Metasploit framework, develop exploits, and generate modules for a variety of real-world scenarios Get this completely updated edition with new useful methods and techniques to make your network robust and resilient Who This Book Is For This book is a hands-on guide to penetration testing using Metasploit and covers its complete development. It shows a number of techniques and methodologies that will help you master the Metasploit framework and explore approaches to carrying out advanced penetration testing in highly secured environments. What You Will Learn Develop advanced and sophisticated auxiliary modules Port exploits from PERL, Python, and many more programming languages Test services such as databases, SCADA, and many more Attack the client side with highly advanced techniques Test mobile and tablet devices with Metasploit Perform social engineering with Metasploit Simulate attacks on web servers and systems with Armitage GUI Script attacks in Armitage using CORTANA *ing In Detail Metasploit is a popular penetration testing framework that has one of the largest exploit databases around. This book will show you exactly how to prepare yourself against the attacks you will face every day by simulating real-world possibilities. We start by reminding you about the basic functionalities of Metasploit and its use in the most traditional ways. You’ll get to know about the basics of programming Metasploit modules as a refresher, and then dive into carrying out exploitation as well building and porting exploits of various kinds in Metasploit. In the next section, you’ll develop the ability to perform testing on various services such as SCADA, databases, IoT, mobile, tablets, and many more services. After this training, we jump into real-world sophisticated scenarios where performing penetration tests are a challenge. With real-life case studies, we take you on a journey through client-side attacks using Metasploit and various *s built on the Metasploit framework. By the end of the book, you will be trained specifically on time-saving techniques using Metasploit. Style and approach This is a step-by-step guide that provides great Metasploit framework methodologies. All the key concepts are explained details with the help of examples and demonstrations that will help you understand everything you need to know about Metasploit.

Examine the techniques and Java tools supporting the growing field of data science About This Book Your entry ticket to the world of data science with the stability and power of Java Explore, analyse, and visualize your data effectively using easy-to-follow examples Make your Java applications more capable using machine learning Who This Book Is For This book is for Java developers who are comfortable developing applications in Java. Those who now want to enter the world of data science or wish to build intelligent applications will find this book ideal. Aspiring data scientists will also find this book very helpful. What You Will Learn Understand the nature and key concepts used in the field of data science Grasp how data is collected, cleaned, and processed Become comfortable with key data analysis techniques See specialized analysis techniques centered on machine learning Master the effective visualization of your data Work with the Java APIs and techniques used to perform data analysis In Detail Data science is concerned with extracting knowledge and insights from a wide variety of data sources to analyse patterns or predict future behaviour. It draws from a wide array of disciplines including statistics, computer science, mathematics, machine learning, and data mining. In this book, we cover the important data science concepts and how they are supported by Java, as well as the often statistically challenging techniques, to provide you with an understanding of their purpose and application. The book starts with an introduction of data science, followed by the basic data science tasks of data collection, data cleaning, data analysis, and data visualization. This is followed by a discussion of statistical techniques and more advanced topics including machine learning, neural networks, and deep learning. The next section examines the major categories of data analysis including text, visual, and audio data, followed by a discussion of resources that support parallel implementation. The final chapter illustrates an in-depth data science problem and provides a comprehensive, Java-based solution. Due to the nature of the topic, simple examples of techniques are presented early followed by a more detailed treatment later in the book. This permits a more natural introduction to the techniques and concepts presented in the book. Style and approach This book follows a tutorial approach, providing examples of each of the major concepts covered. With a step-by-step instructional style, this book covers various facets of data science and will get you up and running quickly.

Get up to date with the finer points of Ubuntu Server using this comprehensive guide About This Book Get well-versed with newly-added features in Ubuntu 16.04 Master the art of installing, managing, and troubleshooting Ubuntu Server A practical easy-to-understand book that will help you enhance your existing skills. Who This Book Is For This book is intended for readers with intermediate or advanced-beginner skills with Linux, who would like to learn all about setting up servers with Ubuntu Server. This book assumes that the reader knows the basics of Linux, such as editing configuration files and running basic commands. What You Will Learn Learn how to manage users, groups, and permissions Encrypt and decrypt disks with Linux Unified Key Setup /Luks Setup SSH for remote access, and connect it to other nodes Understand how to add, remove, and search for packages Use NFS and Samba to share directories with other users Get to know techniques for managing Apache and MariaDB Explore best practices and troubleshooting techniques In Detail Ubuntu is a Debian-based Linux operating system, and has various versions targeted at servers, desktops, phones, tablets and televisions. The Ubuntu Server Edition, also called Ubuntu Server, offers support for several common configurations, and also simplifies common Linux server deployment processes. With this book as their guide, readers will be able to configure and deploy Ubuntu Servers using Ubuntu Server 16.04, with all the skills necessary to manage real servers. The book begins with the concept of user management, group management, as well as file-system permissions. To manage your storage on Ubuntu Server systems, you will learn how to add and format storage and view disk usage. Later, you will also learn how to configure network interfaces, manage IP addresses, deploy Network Manager in order to connect to networks, and manage network interfaces. Furthermore, you will understand how to start and stop services so that you can manage running processes on Linux servers. The book will then demonstrate how to access and share files to or from Ubuntu Servers. You will learn how to create and manage databases using MariaDB and share web content with Apache. To virtualize hosts and applications, you will be shown how to set up KVM/Qemu and Docker and manage virtual machines with virt-manager. Lastly, you will explore best practices and troubleshooting techniques when working with Ubuntu Servers. By the end of the book, you will be an expert Ubuntu Server user well-versed in its advanced concepts. Style and Approach This book is an advanced guide that will show readers how to administer, manage, and deploy Ubuntu server and will also provide expert-level knowledge on advanced security and backup techniques.