Integrate, deploy, rapidly configure, and successfully manage your own big data-intensive clusters in the cloud using OpenStack Sahara About This Book A fast paced guide to help you utilize the benefits of Sahara in OpenStack to meet the Big Data world of Hadoop. A step by step approach to simplify the complexity of Hadoop configuration, deployment and maintenance. Who This Book Is For This book targets data scientists, cloud developers and Devops Engineers who would like to become proficient with OpenStack Sahara. Ideally, this book is well suitable for readers who are familiars with databases, Hadoop and Spark solutions. Additionally, a basic prior knowledge of OpenStack is expected. The readers should also be familiar with different Linux boxes, distributions and virtualization technology. What You Will Learn Integrate and Install Sahara with OpenStack environment Learn Sahara architecture under the hood Rapidly configure and scale Hadoop clusters on top of OpenStack Explore the Sahara REST API to create, deploy and manage a Hadoop cluster Learn the Elastic Processing Data (EDP) facility to execute jobs in clusters from Sahara Cover other Hadoop stable plugins existing supported by Sahara Discover different features provided by Sahara for Hadoop provisioning and deployment Learn how to troubleshoot OpenStack Sahara issues In Detail The Sahara project is a module that aims to simplify the building of data processing capabilities on OpenStack. The goal of this book is to provide a focused, fast paced guide to installing, configuring, and getting started with integrating Hadoop with OpenStack, using Sahara. The book should explain to users how to deploy their data-intensive Hadoop and Spark clusters on top of OpenStack. It will also cover how to use the Sahara REST API, how to develop applications for Elastic Data Processing on Openstack, and setting up hadoop or spark clusters on Openstack. Style and approach This book takes a step by step approach teaching how to integrate, deploy and manage data using OpenStack Sahara. It will teach how the OpenStack Sahara is beneficial by simplifying the complexity of Hadoop configuration, deployment and maintenance.

A handy guide that covers the most essential topics for Salesforce Platform App Builder Certification in an easy-to-understand format About This Book Get to grips with the fundamentals of Force.com to pass the certification exam with flying colors Create Force.com applications, automate business processes, and manage data operations to be a successful Salesforce.com Certified Force.com app builder A step-by-step guide that covers the most essential topics for the Platform App Builder Certification in an easy-to-understand format Who This Book Is For Salesforce beginners who need to prepare for the Salesforce Platform App Builder Certification exam will benefit from this book. This book is ideal for developers and admins who are new to Salesforce CRM and the Force.com platform. It is recommended that users have some basic programming knowledge and are familiar with salesforce. By the end of the book, you will be ready to appear for the exam and develop various applications on the cloud platform. What You Will Learn Learn the basics of the force.com cloud platform Learn to build objects that align with your business Understand the process of building an application on force.com platform Kick-start your certification journey in basic- easy-to-follow guide Focus on important topics that help you accomplish your certification goals Learn to secure your application with the Salesforce security model Manipulate and process large amount of data using the data tools Prepare for the exam with sample mock questions In Detail The Salesforce Certified Platform App Builder exam is for individuals who want to demonstrate their skills and knowledge in designing, building, and implementing custom applications using the declarative customization capabilities of Force.com. This book will build a strong foundation in Force.com to prepare you for the platform app builder certification exam. It will guide you through designing the interface while introducing the Lightning Process Builder. Next, we will implement business logic using various point and click features of Force.com. We will learn to manage data and create reports and dashboards. We will then learn to administer the force.com application by configuring the object-level, field-level, and record-level security. By the end of this book, you will be completely equipped to take the Platform App Builder certification exam. Style and approach Simple and to-the-point examples that can be tried out in your developer org. A practical book for professionals who want to take the Salesforce Platform App Builder Certification exam. Sample questions for every topic in an exam pattern to help you prepare better, and tips to get things started. Full of screen-shots, diagrams, and clear step-by-step instructions that cover the entire syllabus for the exam.

Design and develop high performing programs with Julia About This Book Learn to code high reliability and high performance programs Stand out from the crowd by developing code that runs faster than your peers’ codes This book is intended for developers who are interested in high performance technical programming. Who This Book Is For This book is for beginner and intermediate Julia programmers who are interested in high performance technical computing. You will have a basic familiarity with Julia syntax, and have written some small programs in the language. What You Will Learn Discover the secrets behind Julia’s speed Get a sense of the possibilities and limitations of Julia’s performance Analyze the performance of Julia programs Measure the time and memory taken by Julia programs Create fast machine code using Julia’s type information Define and call functions without compromising Julia’s performance Understand number types in Julia Use Julia arrays to write high performance code Get an overview of Julia’s distributed computing capabilities In Detail Julia is a high performance, high-level dynamic language designed to address the requirements of high-level numerical and scientific computing. Julia brings solutions to the complexities faced by developers while developing elegant and high performing code. Julia High Performance will take you on a journey to understand the performance characteristics of your Julia programs, and enables you to utilize the promise of near C levels of performance in Julia. You will learn to analyze and measure the performance of Julia code, understand how to avoid bottlenecks, and design your program for the highest possible performance. In this book, you will also see how Julia uses type information to achieve its performance goals, and how to use multuple dispatch to help the compiler to emit high performance machine code. Numbers and their arrays are obviously the key structures in scientific computing – you will see how Julia’s design makes them fast. The last chapter will give you a taste of Julia’s distributed computing capabilities. Style and approach This is a hands-on manual that will give you good explanations about the important concepts related to Julia programming.

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.

A light but powerful way to build dynamic real-time applications using ReactJS About This Book Learn how to develop powerful JavaScript applications using ReactJS Integrate a React-based app with an external API (Facebook login) while using React components, with the Facebook developer app Implement the Reactive paradigm to build stateless and asynchronous apps with React Who This Book Is For This book is for any front-end web or mobile-app developer who wants to learn ReactJS. Knowledge of basic JavaScript will give you a good head start with the book. What You Will Learn Understand the ReactJS basics through an overview Install and create your first React component Refactor the ReactJS component using JSX Integrate your React application with the Facebook login and Graph API, then fetch data from your liked pages in Facebook and display them in a browser Handle UI elements events with React, respond to users input, and create stateful components Use some core lifecycle events for integration and find out about ES6 syntaxes in the React world Understand the FLUX architecture and create an application using FLUX with React Make a component more reusable with mixins and validation helpers and structure your components properly Explore techniques to test your ReactJS code Deploy your code using webpack and Gulp In Detail ReactJS, popularly known as the V (view) of the MVC architecture, was developed by the Facebook and Instagram developers. It follows a unidirectional data flow, virtual DOM, and DOM difference that are generously leveraged in order to increase the performance of the UI. Getting Started with React will help you implement the Reactive paradigm to build stateless and asynchronous apps with React. We will begin with an overview of ReactJS and its evolution over the years, followed by building a simple React component. We will then build the same react component with JSX syntax to demystify its usage. You will see how to configure the Facebook Graph API, get your likes list, and render it using React. Following this, we will break the UI into components and you’ll learn how to establish communication between them and respond to users input/events in order to have the UI reflect their state. You’ll also get to grips with the ES6 syntaxes. Moving ahead, we will delve into the FLUX and its architecture, which is used to build client-side web applications and complements React’s composable view components by utilizing a unidirectional data flow. Towards the end, you’ll find out how to make your components reusable, and test and deploy them into a production environment. Finally, we’ll briefly touch on other topics such as React on the server side, Redux and some advanced concepts. Style and approach The book follows a step-by-step, practical, tutorial approach with examples that explain the key concepts of ReactJS. Each topic is sequentially explained and contextually placed to give sufficient details of ReactJS.

A fast-paced administrator's guide to Alfresco from the administration, managing, and high-level design perspectives About This Book Understand system capabilities in order to make informed and appropriate decisions about its administration Manage users, groups, email, file systems, and transformer availability using Alfresco Use Alfresco to capture and efficiently manage information about repositories, servers, and statistics Who This Book Is For The target audience would be users with a basic knowledge of Content Management System, and also users who want to understand Alfresco from the administration and high-level design perspectives. What You Will Learn Understand Alfresco's architecture and important building blocks Learn to install Alfresco on various application servers such as Tomcat , JBoss, and WebLogic. Become familiar with various configurations in Alfresco such as databases, filesystems, email, and audits Administrate Alfresco using the Explorer Admin Console, Share Admin Console, and Workflow Admin Console Understand how to integrate LDAP and Active Directory with Alfresco for centralized user management Learn how Alfresco environments can be clustered for high availability Fully understand how Alfresco stores content and easily retrieve any information from Alfresco Monitor and manage Alfresco systems in production In Detail Alfresco is an open source Enterprise Content Management (ECM) system for Windows and Linux-like operating systems. The year-on-year growth of business connections, contacts, and communications is expanding enterprise boundaries more than ever before. Alfresco enables organizations to collaborate more effectively, improve business process efficiency, and ensure information governance. The basic purpose of Alfresco is to help users to capture and manage information in a better way. It helps you capture, organize, and share binary files. This book will cover the basic building blocks of an Alfresco system, how the components fit together, and the information required to build a system architecture. This book will also focus on security aspects of Alfresco. such as authentication, troubleshooting, managing permissions, and so on. It will also focus on managing content and storage, indexing and searches, setting up clustering for high availability, and so forth. Style and approach A step-by-step guide to understanding the Alfresco system and making informed and appropriate decisions about administration.

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.

Over 50 practical and useful recipes to help you perform data analysis with R by unleashing every native RStudio feature About This Book 54 useful and practical tasks to improve working systems Includes optimizing performance and reliability or uptime, reporting, system management tools, interfacing to standard data ports, and so on Offers 10-15 real-life, practical improvements for each user type Who This Book Is For This book is targeted at R statisticians, data scientists, and R programmers. Readers with R experience who are looking to take the plunge into statistical computing will find this Cookbook particularly indispensable. What You Will Learn Familiarize yourself with the latest advanced R console features Create advanced and interactive graphics Manage your R project and project files effectively Perform reproducible statistical analyses in your R projects Use RStudio to design predictive models for a specific domain-based application Use RStudio to effectively communicate your analyses results and even publish them to a blog Put yourself on the frontiers of data science and data monetization in R with all the tools that are needed to effectively communicate your results and even transform your work into a data product In Detail The requirement of handling complex datasets, performing unprecedented statistical analysis, and providing real-time visualizations to businesses has concerned statisticians and analysts across the globe. RStudio is a useful and powerful tool for statistical analysis that harnesses the power of R for computational statistics, visualization, and data science, in an integrated development environment. This book is a collection of recipes that will help you learn and understand RStudio features so that you can effectively perform statistical analysis and reporting, code editing, and R development. The first few chapters will teach you how to set up your own data analysis project in RStudio, acquire data from different data sources, and manipulate and clean data for analysis and visualization purposes. You'll get hands-on with various data visualization methods using ggplot2, and you will create interactive and multidimensional visualizations with D3.js. Additional recipes will help you optimize your code; implement various statistical models to manage large datasets; perform text analysis and predictive analysis; and master time series analysis, machine learning, forecasting; and so on. In the final few chapters, you'll learn how to create reports from your analytical application with the full range of static and dynamic reporting tools that are available in RStudio so that you can effectively communicate results and even transform them into interactive web applications. Style and approach RStudio is an open source Integrated Development Environment (IDE) for the R platform. The R programming language is used for statistical computing and graphics, which RStudio facilitates and enhances through its integrated environment. This Cookbook will help you learn to write better R code using the advanced features of the R programming language using RStudio. Readers will learn advanced R techniques to compute the language and control object evaluation within R functions. Some of the contents are: Accessing an API with R Substituting missing values by interpolation Performing data filtering activities R Statistical implementation for Geospatial data Developing shiny add-ins to expand RStudio functionalities Using GitHub with RStudio Modelling a recommendation engine with R Using R Markdown for static and dynamic reporting Curating a blog through RStudio Advanced statistical modelling with R and RStudio

Secure your Linux machines and keep them secured with the help of exciting recipes About This Book This book provides code-intensive discussions with detailed recipes that help you understand better and learn faster. More than 50 hands-on recipes to create and administer a secure Linux system locally as well as on a network Enhance file system security and local and remote user authentication by using various security tools and different versions of Linux for different tasks Who This Book Is For Practical Linux Security Cookbook is intended for all those Linux users who already have knowledge of Linux File systems and administration. You should be familiar with basic Linux commands. Understanding Information security and its risks to a Linux system is also helpful in understanding the recipes more easily. However, even if you are unfamiliar with Information security, you will be able to easily follow and understand the recipes discussed. Since Linux Security Cookbook follows a practical approach, following the steps is very easy. What You Will Learn Learn about various vulnerabilities and exploits in relation to Linux systems Configure and build a secure kernel and test it Learn about file permissions and security and how to securely modify files Explore various ways to authenticate local users while monitoring their activities. Authenticate users remotely and securely copy files on remote systems Review various network security methods including firewalls using iptables and TCP Wrapper Explore various security tools including Port Sentry, Squid Proxy, Shorewall, and many more Understand Bash vulnerability/security and patch management In Detail With the growing popularity of Linux, more and more administrators have started moving to the system to create networks or servers for any task. This also makes Linux the first choice for any attacker now. Due to the lack of information about security-related attacks, administrators now face issues in dealing with these attackers as quickly as possible. Learning about the different types of Linux security will help create a more secure Linux system. Whether you are new to Linux administration or experienced, this book will provide you with the skills to make systems more secure. With lots of step-by-step recipes, the book starts by introducing you to various threats to Linux systems. You then get to walk through customizing the Linux kernel and securing local files. Next you will move on to manage user authentication locally and remotely and also mitigate network attacks. Finally, you will learn to patch bash vulnerability and monitor system logs for security. With several screenshots in each example, the book will supply a great learning experience and help you create more secure Linux systems. Style and approach An easy-to-follow cookbook with step-by-step practical recipes covering the various Linux security administration tasks. Each recipe has screenshots, wherever needed, to make understanding more easy.

Your one step guide to learn all about AWS networking. About This Book ? Master your networking skills on Public Cloud. ? Gain hands-on experience of using Amazon VPC, Elastic Load Balancing, Direct Connect and other AWS products. ? Implement troubleshooting skills and best practices for security on AWS network. Who This Book Is For This book is targeted towards cloud architects, cloud solution providers, or any stakeholders dealing with networking on AWS Cloud. A prior idea of Amazon Web Services will be an added advantage. What You Will Learn ? Overview of all networking services available in AWS. ? Gain Work with load balance application across different regions. ? Learn auto scale instance based on the increase and decrease of the traffic. ? Deploy application in highly available and fault tolerant manner. ? Configure Route 53 for a web application. ? Troubleshooting tips and best practices at the end In Detail Amazon Web Services (AWS) dominates the public cloud market by a huge margin and it continues to be the first choice for many organizations. Networking has been an area of focus for all the leading cloud service providers. AWS has a suite of network-related products that help to perform network-related task in AWS. This book initially covers the basics of networking in AWS. Then we use AWS VPC to create an isolated virtual cloud for performing network-related tasks. We then provide an overview of AWS Direct Connect after taking a deep dive into scalability and load balancing using Auto scaling feature, Elastic Load Balancing, and Amazon Route S3. Toward the end of the book, we cover some troubleshooting tips and security best practices for your network. By the end of this book, you will have hands-on experience of working with network tasks on AWS. Style and approach A step by step practical guide that helps you use all networking services available in AWS effectively.

A perfect guide to speed up the predicting power of machine learning algorithms About This Book ? Design, discover, and create dynamic, efficient features for your machine learning application ? Understand your data in-depth and derive astonishing data insights with the help of this Guide ? Grasp powerful feature-engineering techniques and build machine learning systems Who This Book Is For If you are a data science professional or a machine learning engineer looking to strengthen your predictive analytics model, then this book is a perfect guide for you. Some basic understanding of the machine learning concepts and Python *ing would be enough to get started with this book. What You Will Learn ? Identify and leverage different feature types ? Clean features in data to improve predictive power ? Understand why and how to perform feature selection, and model error analysis ? Leverage domain knowledge to construct new features ? Deliver features based on mathematical insights ? Use machine-learning algorithms to construct features ? Master feature engineering and optimization ? Harness feature engineering for real world applications through a structured case study In Detail Feature engineering is the most important step in creating powerful machine learning systems. This book will take you through the entire feature-engineering journey to make your machine learning much more systematic and effective. You will start with understanding your data—often the success of your ML models depends on how you leverage different feature types, such as continuous, categorical, and more, You will learn when to include a feature, when to omit it, and why, all by understanding error analysis and the acceptability of your models. You will learn to convert a problem statement into useful new features. You will learn to deliver features driven by business needs as well as mathematical insights. You'll also learn how to use machine learning on your machines, automatically learning amazing features for your data. By the end of the book, you will become proficient in Feature Selection, Feature Learning, and Feature Optimization. Style and approach This step-by-step guide with use cases, examples, and illustrations will help you master the concepts of feature engineering. Along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts later on and will help you implement these techniques in the real world.

Build, scale, and deploy deep neural network models using the star libraries in Python About This Book ? Delve into advanced machine learning and deep learning use cases using Tensorflow and Keras ? Build, deploy, and scale end-to-end deep neural network models in a production environment ? Learn to deploy TensorFlow on mobile, and distributed TensorFlow on GPU, Clusters, and Kubernetes Who This Book Is For This book is for data scientists, machine learning engineers, artificial intelligence engineers, and for all TensorFlow users who wish to upgrade their TensorFlow knowledge and work on various machine learning and deep learning problems. If you are looking for an easy-to-follow guide that underlines the intricacies and complex use cases of machine learning, you will find this book extremely useful. Some basic understanding of TensorFlow is required to get the most out of the book. What You Will Learn ? Master advanced concepts of deep learning such as transfer learning, reinforcement learning, generative models and more, using TensorFlow and Keras ? Perform supervised (classification and regression) and unsupervised (clustering) learning to solve machine learning tasks ? Build end-to-end deep learning (CNN, RNN, and Autoencoders) models with TensorFlow ? Scale and deploy production models with distributed and high-performance computing on GPU and clusters ? Build TensorFlow models to work with multilayer perceptrons using Keras, TFLearn, and R ? Learn the functionalities of smart apps by building and deploying TensorFlow models on iOS and Android devices ? Supercharge TensorFlow with distributed training and deployment on Kubernetes and TensorFlow Clusters In Detail TensorFlow is the most popular numerical computation library built from the ground up for distributed, cloud, and mobile environments. TensorFlow represents the data as tensors and the computation as graphs. This book is a comprehensive guide that lets you explore the advanced features of TensorFlow 1.x. Gain insight into TensorFlow Core, Keras, TF Estimators, TFLearn, TF Slim, Pretty Tensor, and Sonnet. Leverage the power of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Throughout the book, you will obtain hands-on experience with varied datasets, such as MNIST, CIFAR-10, PTB, text8, and COCO-Images. You will learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF Clusters, deploy production models with TensorFlow Serving, and build and deploy TensorFlow models for mobile and embedded devices on Android and iOS platforms. You will see how to call TensorFlow and Keras API within the R statistical software, and learn the required techniques for debugging when the TensorFlow API-based code does not work as expected. The book helps you obtain in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problems. By the end of this guide, you will have mastered the offerings of TensorFlow and Keras, and gained the skills you need to build smarter, faster, and efficient machine learning and deep learning systems. Style and approach Step-by-step comprehensive guide filled with advanced, real-world examples to help you master Tensorflow 1.x

Design, build and test RESTful web services with the Django framework and Python About This Book ? Create efficient real-world RESTful web services with the latest Django framework ? Authenticate, secure, and integrate third-party packages efficiently in your Web Services ? Leverage the power of Python for faster Web Service development Who This Book Is For This book is for Python developers who want to create RESTful web services with Django; you need to have a basic working knowledge of Django but no previous experience with RESTful web services is required. What You Will Learn ? The best way to build a RESTful Web Service or API with Django and the Django REST Framework ? Develop complex RESTful APIs from scratch with Django and the Django REST Framework ? Work with either SQL or NoSQL data sources ? Design RESTful Web Services based on application requirements ? Use third-party packages and extensions to perform common tasks ? Create automated tests for RESTful web services ? Debug, test, and profile RESTful web services with Django and the Django REST Framework In Detail Django is a Python web framework that makes the web development process very easy. It reduces the amount of trivial code, which simplifies the creation of web applications and results in faster development. It is very powerful and a great choice for creating RESTful web services. If you are a Python developer and want to efficiently create RESTful web services with Django for your apps, then this is the right book for you. The book starts off by showing you how to install and configure the environment, required software, and tools to create RESTful web services with Django and the Django REST framework. We then move on to working with advanced serialization and migrations to interact with SQLite and non-SQL data sources. We will use the features included in the Django REST framework to improve our simple web service. Further, we will create API views to process diverse HTTP requests on objects, go through relationships and hyperlinked API management, and then discover the necessary steps to include security and permissions related to data models and APIs. We will also apply throttling rules and run tests to check that versioning works as expected. Next we will run automated tests to improve code coverage. By the end of the book, you will be able to build RESTful web services with Django." Style and approach The book takes a straightforward approach, giving you the techniques and best use cases to build great web services with Django and Python

A comprehensive guide to mastering the art of preventing your Linux system from getting compromised. About This Book ? Leverage this guide to confidently deliver a system that reduces the risk of being hacked ? Perform a number of advanced Linux security techniques such as network service detection, user authentication, controlling special permissions, encrypting file systems, and much more ? Master the art of securing a Linux environment with this end-to-end practical guide Who This Book Is For If you are a systems administrator or a network engineer interested in making your Linux environment more secure, then this book is for you. Security consultants wanting to enhance their Linux security skills will also benefit from this book. Prior knowledge of Linux is mandatory. What You Will Learn ? Use various techniques to prevent intruders from accessing sensitive data ? Prevent intruders from planting malware, and detect whether malware has been planted ? Prevent insiders from accessing data that they aren’t authorized to access ? Do quick checks to see whether a computer is running network services that it doesn’t need to run ? Learn security techniques that are common to all Linux distros, and some that are distro-specific In Detail This book has extensive coverage of techniques that will help prevent attackers from breaching your system, by building a much more secure Linux environment. You will learn various security techniques such as SSH hardening, network service detection, setting up firewalls, encrypting file systems, protecting user accounts, authentication processes, and so on. Moving forward, you will also develop hands-on skills with advanced Linux permissions, access control, special modes, and more. Lastly, this book will also cover best practices and troubleshooting techniques to get your work done efficiently. By the end of this book, you will be confident in delivering a system that will be much harder to compromise. Style and approach An advanced-level guide filled with real-world examples that will help you secure your Linux system

Create fast and efficient server-side applications using the latest features of Odoo v11 About This Book ? Get the most up-to-date guide on Odoo 11 to create custom and reusable modules ? Interconnect your application with other systems by implementing web APIs ? Understand the mechanisms powering the Odoo framework to build robust enterprises Who This Book Is For If you're a Python developer and want to develop highly efficient business applications with the latest Odoo framework (or if you just want a hands on problem solution book for all your Odoo Development related issues), this book is for you! Some experience with the JavaScript programming language and web development is required to get the most out of this book. 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 ? Add automated tests and learn how to debug Odoo apps ? Learn about the access security model and internationalization features ? Customize websites built with Odoo, by writing your own templates and providing new snippets for use in the website builder ? Extend the web client with new widgets and make RPC calls to the server In Detail Odoo is a full-featured open source ERP with a focus on extensibility. The flexibility and sustainability of open source are 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. Version 11 offers better usability and speed: a new design (as compared to the current Odoo Enterprise version) and a mobile interface. The book starts by covering Odoo installation and administration and Odoo Server deployment. It then delves into the implementation of Odoo modules, the different inheritance models available in Odoo. You will then learn how to define access rules for your data; how to make your application available in different languages; how to expose your data models to end users on the back end and on the front end; and how to create beautiful PDF versions of your data. By the end of the book, you will have a thorough knowledge of Odoo and will be able to build effective applications by applying Odoo development best practices Style and Approach This recipe-based practical guide presents each topic with step-by-step instructions on how you can create fast and efficient server-side applications using the latest features of Odoo v11

Learn to design, implement and secure your IoT infrastructure About This Book ? Build a complete IoT system that is the best fit for your organization ? Learn about different concepts, technologies, and tradeoffs in the IoT architectural stack ? Understand the theory, concepts, and implementation of each element that comprises IoT design—from sensors to the cloud ? Implement best practices to ensure the reliability, scalability, robust communication systems, security, and data analysis in your IoT infrastructure Who This Book Is For This book is for architects, system designers, technologists, and technology managers who want to understand the IoT ecosphere, various technologies, and tradeoffs and develop a 50,000-foot view of IoT architecture. What You Will Learn ? Understand the role and scope of architecting a successful IoT deployment, from sensors to the cloud ? Scan the landscape of IoT technologies that span everything from sensors to the cloud and everything in between ? See the trade-offs in choices of protocols and communications in IoT deployments ? Build a repertoire of skills and the vernacular necessary to work in the IoT space ? Broaden your skills in multiple engineering domains necessary for the IoT architect In Detail The Internet of Things (IoT) is the fastest growing technology market. Industries are embracing IoT technologies to improve operational expenses, product life, and people's well-being. An architectural guide is necessary if you want to traverse the spectrum of technologies needed to build a successful IoT system, whether that's a single device or millions of devices. This book encompasses the entire spectrum of IoT solutions, from sensors to the cloud. We start by examining modern sensor systems and focus on their power and functionality. After that, we dive deep into communication theory, paying close attention to near-range PAN, including the new Bluetooth? 5.0 specification and mesh networks. Then, we explore IP-based communication in LAN and WAN, including 802.11ah, 5G LTE cellular, SigFox, and LoRaWAN. Next, we cover edge routing and gateways and their role in fog computing, as well as the messaging protocols of MQTT and CoAP. With the data now in internet form, you'll get an understanding of cloud and fog architectures, including the OpenFog standards. We wrap up the analytics portion of the book with the application of statistical analysis, complex event processing, and deep learning models. Finally, we conclude by providing a holistic view of the IoT security stack and the anatomical details of IoT exploits while countering them with software defined perimeters and blockchains. Style and approach This hands-on guide combines theory and application to the Internet of Things. This book covers the entire architectural stack of components and engineering domains from sensors to power analysis, communication systems, information theory, networking and routing, data security, protocols, software stacks, cloud mechanics, and data analytics with deep learning.

Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasks About This Book ? Train different kinds of deep learning model from scratch to solve specific problems in Computer Vision ? Combine the power of Python, Keras, and TensorFlow to build deep learning models for object detection, image classification, similarity learning, image captioning, and more ? Includes tips on optimizing and improving the performance of your models under various constraints Who This Book Is For This book is targeted at data scientists and Computer Vision practitioners who wish to apply the concepts of Deep Learning to overcome any problem related to Computer Vision. A basic knowledge of programming in Python—and some understanding of machine learning concepts—is required to get the best out of this book. What You Will Learn ? Set up an environment for deep learning with Python, TensorFlow, and Keras ? Define and train a model for image and video classification ? Use features from a pre-trained Convolutional Neural Network model for image retrieval ? Understand and implement object detection using the real-world Pedestrian Detection scenario ? Learn about various problems in image captioning and how to overcome them by training images and text together ? Implement similarity matching and train a model for face recognition ? Understand the concept of generative models and use them for image generation ? Deploy your deep learning models and optimize them for high performance In Detail Deep learning has shown its power in several application areas of Artificial Intelligence, especially in Computer Vision. Computer Vision is the science of understanding and manipulating images, and finds enormous applications in the areas of robotics, automation, and so on. This book will also show you, with practical examples, how to develop Computer Vision applications by leveraging the power of deep learning. In this book, you will learn different techniques related to object classification, object detection, image segmentation, captioning, image generation, face analysis, and more. You will also explore their applications using popular Python libraries such as TensorFlow and Keras. This book will help you master state-of-the-art, deep learning algorithms and their implementation. Style and approach This book will teach advanced techniques for Computer Vision, applying the deep learning model in reference to various datasets.

Design and administer enterprise-grade MySQL 8 solutions About This Book ? Store, retrieve, and manipulate your data using the latest MySQL 8 features ? Practical recipes on effective administration in MySQL, with a focus on security, performance tuning, troubleshooting, and more ? Contains tips, tricks, and best practices for designing, developing, and administering your MySQL 8 database solution without any hassle Who This Book Is For If you are a MySQL developer or administrator looking for quick, handy solutions to solve the most common and not-so-common problems in MySQL, this book is for you. MySQL DBAs looking to get up-to-speed with the latest MySQL 8 development and administration features will also find this book very useful. Prior knowledge of Linux and RDBMS is desirable. What You Will Learn ? Install and configure your MySQL 8 instance without any hassle ? Get to grips with new features of MySQL 8 like CTE, Window functions and many more ? Perform backup tasks, recover data and set up various replication topologies for your database ? Maximize performance by using new features of MySQL 8 like descending indexes, controlling query optimizer and resource groups ? Learn how to use general table space to suit the SaaS or multi-tenant applications ? Analyze slow queries using performance schema, sys schema and third party tools ? Manage and monitor your MySQL instance and implement efficient performance-tuning tasks In Detail MySQL is one of the most popular and widely used relational databases in the World today. The recently released MySQL 8 version promises to be better and more efficient than ever before. This book contains everything you need to know to be the go-to person in your organization when it comes to MySQL. Starting with a quick installation and configuration of your MySQL instance, the book quickly jumps into the querying aspects of MySQL. It shows you the newest improvements in MySQL 8 and gives you hands-on experience in managing high-transaction and real-time datasets. If you've already worked with MySQL before and are looking to migrate your application to MySQL 8, this book will also show you how to do that. The book also contains recipes on efficient MySQL administration, with tips on effective user management, data recovery, security, database monitoring, performance tuning, troubleshooting, and more. With quick solutions to common and not-so-common problems you might encounter while working with MySQL 8, the book contains practical tips and tricks to give you the edge over others in designing, developing, and administering your database effectively. Style and approach This book takes a recipe-based approach to tackling the pain points of SQL developers. It is a comprehensive book full of solutions to common problems faced by SQL administrators and developers alike.

Build smart, efficient, and fast enterprise-grade web implementation of the microservices architecture that can be easily scaled. About This Book ? Write easy-to-maintain lean and clean code with Kotlin for developing better microservices ? Scale your Microserivces in your own cloud with Docker and Docker Swarm ? Explore Spring 5 functional reactive web programming with Spring WebFlux Who This Book Is For If you are a Kotlin developer with a basic knowledge of microservice architectures and now want to effectively implement these services on enterprise-level web applications, then this book is for you What You Will Learn ? Understand microservice architectures and principles ? Build microservices in Kotlin using Spring Boot 2.0 and Spring Framework 5.0 ? Create reactive microservices that perform non-blocking operations with Spring WebFlux ? Use Spring Data to get data reactively from MongoDB ? Test effectively with JUnit and Kotlin ? Create cloud-native microservices with Spring Cloud ? Build and publish Docker images of your microservices ? Scaling microservices with Docker Swarm ? Monitor microservices with JMX ? Deploy microservices in OpenShift Online In Detail With Google's inclusion of first-class support for Kotlin in their Android ecosystem, Kotlin's future as a mainstream language is assured. Microservices help design scalable, easy-to-maintain web applications; Kotlin allows us to take advantage of modern idioms to simplify our development and create high-quality services. With 100% interoperability with the JVM, Kotlin makes working with existing Java code easier. Well-known Java systems such as Spring, Jackson, and Reactor have included Kotlin modules to exploit its language features. This book guides the reader in designing and implementing services, and producing production-ready, testable, lean code that's shorter and simpler than a traditional Java implementation. Reap the benefits of using the reactive paradigm and take advantage of non-blocking techniques to take your services to the next level in terms of industry standards. You will consume NoSQL databases reactively to allow you to create high-throughput microservices. Create cloud-native microservices that can run on a wide range of cloud providers, and monitor them. You will create Docker containers for your microservices and scale them. Finally, you will deploy your microservices in OpenShift Online. Style and approach This book guides the reader in designing and implementing services, achieving production- ready, testable, easy-to-maintain, lean code that's shorter and simpler than a traditional Java implementation.

Get more control of your applications performances in development and production and know how to meet your Service Level Agreement on critical microservices. About This Book ? Learn how to write a JavaEE application with performance constraints (Service Level Agreement—SLA) leveraging the platform ? Learn how to identify bottlenecks and hotspots in your application to fix them ? Ensure that you are able to continuously control your performance in production and during development Who This Book Is For If you're a Java developer looking to improve the performance of your code or simply wanting to take your skills up to the next level, then this book is perfect for you. What You Will Learn ? Identify performance bottlenecks in an application ? Locate application hotspots using performance tools ? Understand the work done under the hood by EE containers and its impact on performance ? Identify common patterns to integrate with Java EE applications ? Implement transparent caching on your applications ? Extract more information from your applications using Java EE without modifying existing code ? Ensure constant performance and eliminate regression In Detail The ease with which we write applications has been increasing, but with this comes the need to address their performance. A balancing act between easily implementing complex applications and keeping their performance optimal is a present-day need. In this book, we explore how to achieve this crucial balance while developing and deploying applications with Java EE 8. The book starts by analyzing various Java EE specifications to identify those potentially affecting performance adversely. Then, we move on to monitoring techniques that enable us to identify performance bottlenecks and optimize performance metrics. Next, we look at techniques that help us achieve high performance: memory optimization, concurrency, multi-threading, scaling, and caching. We also look at fault tolerance solutions and the importance of logging. Lastly, you will learn to benchmark your application and also implement solutions for continuous performance evaluation. By the end of the book, you will have gained insights into various techniques and solutions that will help create high-performance applications in the Java EE 8 environment. Style and approach This book will cover vital concepts implemented through a sample application built throughout the book. This will enable you to apply these concepts to suit your software requirements.

Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming. About This Book ? Explore machine learning techniques with prominent open source Scala libraries such as Spark ML, H2O, MXNet, Zeppelin, and DeepLearning4j ? Solve real-world machine learning problems by delving complex numerical computing with Scala functional programming in a scalable and faster way ? Cover all key aspects such as collection, storing, processing, analyzing, and evaluation required to build and deploy machine models on computing clusters using Scala Play framework. Who This Book Is For If you want to leverage the power of both Scala and Spark to make sense of Big Data, then this book is for you. If you are well versed with machine learning concepts and wants to expand your knowledge by delving into the practical implementation using the power of Scala, then this book is what you need! Strong understanding of Scala Programming language is recommended. Basic familiarity with machine Learning techniques will be more helpful. What You Will Learn ? Apply advanced regression techniques to boost the performance of predictive models ? Use different classification algorithms for business analytics ? Generate trading strategies for Bitcoin and stock trading using ensemble techniques ? Train Deep Neural Networks (DNN) using H2O and Spark ML ? Utilize NLP to build scalable machine learning models ? Learn how to apply reinforcement learning algorithms such as Q-learning for developing ML application ? Learn how to use autoencoders to develop a fraud detection application ? Implement LSTM and CNN models using DeepLearning4j and MXNet In Detail 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. Style and approach Leverage the power of machine learning and deep learning in different domains, giving best practices and tips from a real world case studies and help you to avoid pitfalls and fallacies towards decision making based on predictive analytics with ML models.