Master machine learning techniques with real-world projects that interface TensorFlow with R, H2O, MXNet, and other languages Key Features * Gain expertise in machine learning, deep learning and other techniques * Build intelligent end-to-end projects for finance, social media, and a variety of domains * Implement multi-class classification, regression, and clustering Book Description R is one of the most popular languages when it comes to exploring the mathematical side of machine learning and easily performing computational statistics. This Learning Path shows you how to leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization. You'll tackle realistic projects such as building powerful machine learning models with ensembles to predict employee attrition. You'll explore different clustering techniques to segment customers using wholesale data and use TensorFlow and Keras-R for performing advanced computations. You’ll also be introduced to reinforcement learning along with its various use cases and models. Additionally, it shows you how some of these black-box models can be diagnosed and understood. By the end of this Learning Path, you’ll be equipped with the skills you need to deploy machine learning techniques in your own projects. This Learning Path includes content from the following Packt products: * R Machine Learning Projects by Dr. Sunil Kumar Chinnamgari * Mastering Machine Learning with R - Third Edition by Cory Lesmeister What you will learn * Develop a joke recommendation engine to recommend jokes that match users’ tastes * Build autoencoders for credit card fraud detection * Work with image recognition and convolutional neural networks * Make predictions for casino slot machine using reinforcement learning * Implement NLP techniques for sentiment analysis and customer segmentation * Produce simple and effective data visualizations for improved insights * Use NLP to extract insights for text * Implement tree-based classifiers including random forest and boosted tree Who this book is for If you are a data analyst, data scientist, or machine learning developer this is an ideal Learning Path for you. Each project will help you test your skills in implementing machine learning algorithms and techniques. A basic understanding of machine learning and working knowledge of R programming is necessary to get the most out of this Learning Path.

Apply modern reinforcement learning and deep reinforcement learning methods using Python and its powerful libraries Key Features * Your entry point into the world of artificial intelligence using the power of Python * An example-rich guide to master various RL and DRL algorithms * Explore the power of modern Python libraries to gain confidence in building self-trained applications Book Description Reinforcement Learning (RL) is the trending and most promising branch of artificial intelligence. This Learning Path will help you master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms. The Learning Path starts with an introduction to RL followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration. You'll also work on various datasets including image, text, and video. This example-rich guide will introduce you to deep RL algorithms, such as Dueling DQN, DRQN, A3C, PPO, and TRPO. You will gain experience in several domains, including gaming, image processing, and physical simulations. You'll explore TensorFlow and OpenAI Gym to implement algorithms that also predict stock prices, generate natural language, and even build other neural networks. You will also learn about imagination-augmented agents, learning from human preference, DQfD, HER, and many of the recent advancements in RL. By the end of the Learning Path, you will have all the knowledge and experience needed to implement RL and deep RL in your projects, and you enter the world of artificial intelligence to solve various real-life problems. This Learning Path includes content from the following Packt products: * Hands-On Reinforcement Learning with Python by Sudharsan Ravichandiran * Python Reinforcement Learning Projects by Sean Saito, Yang Wenzhuo, and Rajalingappaa Shanmugamani What you will learn * Train an agent to walk using OpenAI Gym and TensorFlow * Solve multi-armed-bandit problems using various algorithms * Build intelligent agents using the DRQN algorithm to play the Doom game * Teach your agent to play Connect4 using AlphaGo Zero * Defeat Atari arcade games using the value iteration method * Discover how to deal with discrete and continuous action spaces in various environments Who this book is for If you’re an ML/DL enthusiast interested in AI and want to explore RL and deep RL from scratch, this Learning Path is for you. Prior knowledge of linear algebra is expected.

Design, deploy, and manage large-scale containers using Kubernetes Key Features * Gain insight into the latest features of Kubernetes, including Prometheus and API aggregation * Discover ways to keep your clusters always available, scalable, and up-to-date * Master the skills of designing and deploying large clusters on various cloud platforms Book Description If you are running a number of containers and want to be able to automate the way they’re managed, it can be helpful to have Kubernetes at your disposal. This Learning Path guides you through core Kubernetes constructs, such as pods, services, replica sets, replication controllers, and labels. You'll get started by learning how to integrate your build pipeline and deployments in a Kubernetes cluster. As you cover more chapters in the Learning Path, you'll get up to speed with orchestrating updates behind the scenes, avoiding downtime on your cluster, and dealing with underlying cloud provider instability in your cluster. With the help of real-world use cases, you'll also explore options for network configuration, and understand how to set up, operate, and troubleshoot various Kubernetes networking plugins. In addition to this, you'll gain insights into custom resource development and utilization in automation and maintenance workflows. By the end of this Learning Path, you'll have the expertise you need to progress from an intermediate to an advanced level of understanding Kubernetes. This Learning Path includes content from the following Packt products: * Getting Started with Kubernetes - Third Edition by Jonathan Baier and Jesse White * Mastering Kubernetes - Second Edition by Gigi Sayfan What you will learn * Download, install, and configure the Kubernetes code base * Create and configure custom Kubernetes resources * Use third-party resources in your automation workflows * Deliver applications as standard packages * Set up and access monitoring and logging for Kubernetes clusters * Set up external access to applications running in the cluster * Manage and scale Kubernetes with hosted platforms on Amazon Web Services (AWS), Azure, and Google Cloud Platform (GCP) * Run multiple clusters and manage them from a single control plane Who this book is for If you are a developer or a system administrator with an intermediate understanding of Kubernetes and want to master its advanced features, then this book is for you. Basic knowledge of networking is required to easily understand the concepts explained.

Learn end-to-end automation testing techniques for web and mobile browsers using Selenium WebDriver, AppiumDriver, Java, and TestNG Key Features * Explore the Selenium grid architecture and build your own grid for browser and mobile devices * Use ExtentReports for processing results and SauceLabs for cloud-based test services * Unlock the full potential of Selenium to test your web applications. Book Description Selenium WebDriver 3.x is an open source API for testing both browser and mobile applications. With the help of this book, you can build a solid foundation and can easily perform end-to-end testing on web and mobile browsers.You'll begin by being introduced to the Selenium Page Object Model for software development. You'll architect your own framework with a scalable driver class, Java utility classes, and support for third-party tools and plugins. You'll design and build a Selenium grid from scratch to enable the framework to scale and support different browsers, mobile devices, and platforms.You'll strategize and handle a rich web UI using the advanced WebDriver API and learn techniques to handle real-time challenges in WebDriver. You'll perform different types of testing, such as cross-browser testing, load testing, and mobile testing. Finally, you will also be introduced to data-driven testing, using TestNG to create your own automation framework.By the end of this Learning Path, you'll be able to design your own automation testing framework and perform data-driven testing with Selenium WebDriver. This Learning Path includes content from the following Packt products: * Selenium WebDriver 3 Practical Guide - Second Edition by Unmesh Gundecha * Selenium Framework Design in Data-Driven Testing by Carl Cocchiaro What you will learn * Use different mobile and desktop browser platforms with Selenium 3 * Use the Actions API for performing various keyboard and mouse actions * Design the Selenium Driver Class for local, remote, and third-party grid support * Build page object classes with the Selenium Page Object Model * Develop data-driven test classes using the TestNG framework * Encapsulate data using the JSON protocol * Build a Selenium Grid for RemoteWebDriver testing * Build and use utility classes in synchronization, file I/O, reporting and test listener classes Who this book is for This Learning Path is ideal for software quality assurance/testing professionals, software project managers, or software developers interested in using Selenium for testing their applications. Professionals responsible for designing and building enterprise-based testing frameworks will also find this Learning Path useful. Prior programming experience in Java are TestNG is necessary.

Use an open source firewall and features such as failover, load balancer, OpenVPN, IPSec, and Squid to protect your network Key Features *Explore pfSense, a trusted open source network security solution *Configure pfSense as a firewall and create and manage firewall rules *Test pfSense for failover and load balancing across multiple WAN connections Book Description While connected to the internet, you’re a potential target for an array of cyber threats, such as hackers, keyloggers, and Trojans that attack through unpatched security holes. A firewall works as a barrier (or ‘shield’) between your computer and cyberspace. pfSense is highly versatile firewall software. With thousands of enterprises using pfSense, it is fast becoming the world's most trusted open source network security solution. Network Security with pfSense begins with an introduction to pfSense, where you will gain an understanding of what pfSense is, its key features, and advantages. Next, you will learn how to configure pfSense as a firewall and create and manage firewall rules. As you make your way through the chapters, you will test pfSense for failover and load balancing across multiple wide area network (WAN) connections. You will then configure pfSense with OpenVPN for secure remote connectivity and implement IPsec VPN tunnels with pfSense. In the concluding chapters, you’ll understand how to configure and integrate pfSense as a Squid proxy server. By the end of this book, you will be able to leverage the power of pfSense to build a secure network. What you will learn *Understand what pfSense is, its key features, and advantages *Configure pfSense as a firewall *Set up pfSense for failover and load balancing *Connect clients through an OpenVPN client *Configure an IPsec VPN tunnel with pfSense *Integrate the Squid proxy into pfSense Who this book is for Network Security with pfSense is for IT administrators, security administrators, technical architects, chief experience officers, and individuals who own a home or small office network and want to secure it.

If your application source code is overly verbose, it can be a nightmare to maintain. Write concise and expressive, type-safe code in an environment that lets you build for the JVM, browser, and more. Key Features *Expert guidance that shows you to efficiently use both object-oriented and functional programming techniques *Understand functional programming libraries, such as Cats and Scalaz, and use them to augment your Scala development *Perfectly balances theory and hands-on exercises, assessments, and activities Book Description This book teaches you how to build and contribute to Scala programs, recognizing common patterns and techniques used with the language. You’ll learn how to write concise, functional code with Scala. After an introduction to core concepts, syntax, and writing example applications with scalac, you’ll learn about the Scala Collections API and how the language handles type safety via static types out-of-the-box. You’ll then learn about advanced functional programming patterns, and how you can write your own Domain Specific Languages (DSLs). By the end of the book, you’ll be equipped with the skills you need to successfully build smart, efficient applications in Scala that can be compiled to the JVM. What you will learn *Understand the key language syntax and core concepts for application development *Master the type system to create scalable type-safe applications while cutting down your time spent debugging *Understand how you can work with advanced data structures via built-in features such as the Collections library *Use classes, objects, and traits to transform a trivial chatbot program into a useful assistant *Understand what are pure functions, immutability, and higher-order functions *Recognize and implement popular functional programming design patterns Who this book is for This is an ideal book for developers who are looking to learn Scala, and is particularly well suited for Java developers looking to migrate across to Scala for application development on the JVM.

A fast-paced guide to putting your GeoServer-based application into fast, user-friendly, and secure production Key Features * Resolve bottlenecks, optimize data stores, and cluster server resources * Use identity management and authentication for a user-specific, secure web application * Go beyond traditional web hosting to explore the full range of hosting options in the cloud Book Description GeoServer is open source, server-side software written in Java that allows users to share and edit geospatial data. In this book, you'll start by learning how to develop a spatial analysis platform with web processing services. Then you'll see how to develop an algorithm by chaining together geospatial analysis processes, which you can share with anyone in the world. Next you'll delve into a very important technique to improve the speed of your map application—tile caching. Here, you'll understand how tile caching works, how to develop an effective tile cache-supported web service, and how to leverage tile caching in your OpenLayers web application. Further on, you'll explore important tweaks to produce a performant GeoServer-backed web mapping application. Moving on, you'll enable authentication on the frontend and backend to protect sensitive map data, and deliver sensitive data to your end user. Finally, you'll see how to put your web application into production in a secure and user-friendly way. You'll go beyond traditional web hosting to explore the full range of hosting options in the cloud, and maintain a reliable server instance. What you will learn * Develop a WPS-processing service to allow web-based geospatial data processing * Get to know important techniques to improve the speed of your web map application—tile caching, raster data optimization, and server clustering * Find out which GeoServer settings resolve bottlenecks * Develop an algorithm by chaining geospatial analysis processes together * Put your application into production with hosting, monitoring, and automated backup and recovery * Understand how to develop an effective tile cache-supported web service * Master techniques that ensure resilient server deployment Who this book is for This book is for anyone who wants to learn about advanced interfaces, security, and troubleshooting techniques in GeoServer. A basic understanding of GeoServer is required

If you are a web developer with some experience in JavaScript and want to enter the world of modern web applications, then this book is ideal for you. Learning how to leverage the three tools (Yo, Bower, and Grunt) in the Yeoman workflow will be perfect as your next step towards building scalable, dynamic, and modern web applications for just about any platform.

VMware vSphere 6.5: Deployment, Migration, Patch-Management

A solution-based guide to put your deep learning models into production with the power of Apache Spark Key Features * Discover practical recipes for distributed deep learning with Apache Spark * Learn to use libraries such as Keras and TensorFlow * Solve problems in order to train your deep learning models on Apache Spark Book Description With deep learning gaining rapid mainstream adoption in modern-day industries, organizations are looking for ways to unite popular big data tools with highly efficient deep learning libraries. As a result, this will help deep learning models train with higher efficiency and speed. With the help of the Apache Spark Deep Learning Cookbook, you’ll work through specific recipes to generate outcomes for deep learning algorithms, without getting bogged down in theory. From setting up Apache Spark for deep learning to implementing types of neural net, this book tackles both common and not so common problems to perform deep learning on a distributed environment. In addition to this, you’ll get access to deep learning code within Spark that can be reused to answer similar problems or tweaked to answer slightly different problems. You will also learn how to stream and cluster your data with Spark. Once you have got to grips with the basics, you’ll explore how to implement and deploy deep learning models, such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) in Spark, using popular libraries such as TensorFlow and Keras. By the end of the book, you'll have the expertise to train and deploy efficient deep learning models on Apache Spark. What you will learn * Set up a fully functional Spark environment * Understand practical machine learning and deep learning concepts * Apply built-in machine learning libraries within Spark * Explore libraries that are compatible with TensorFlow and Keras * Explore NLP models such as Word2vec and TF-IDF on Spark * Organize dataframes for deep learning evaluation * Apply testing and training modeling to ensure accuracy * Access readily available code that may be reusable Who this book is for If you’re looking for a practical and highly useful resource for implementing efficiently distributed deep learning models with Apache Spark, then the Apache Spark Deep Learning Cookbook is for you. Knowledge of the core machine learning concepts and a basic understanding of the Apache Spark framework is required to get the best out of this book. Additionally, some programming knowledge in Python is a plus.

Leverage the power of Hyperledger Fabric to develop Blockchain-based distributed ledgers with ease About This Book ? Write your own chaincode/smart contracts using Golang on hyperledger network ? Build and deploy decentralized applications (DApps) ? Dive into real world blockchain challenges such as integration and scalability Who This Book Is For The book benefits business leaders as it provides a comprehensive view on blockchain business models, governance structure, and business design considerations of blockchain solutions. Technology leaders stand to gain a lot from the detailed discussion around the technology landscape, technology design, and architecture considerations in the book. With model-driven application development, this guide will speed up understanding and concept development for blockchain application developers. The simple and well organized content will put novices at ease with blockchain concepts and constructs. What You Will Learn ? Discover why blockchain is a game changer in the technology landscape ? Set up blockchain networks using basic Hyperledger Fabric deployment ? Understand the considerations for creating decentralized applications ? Learn the process of creating good business networks using Hyperledger ? Write Smart Contracts quickly with Hyperledger Composer ? Design transaction model and chaincode with Golang ? Deploy Composer REST Gateway to access the Composer transactions ? Discern how business network impacts your Hyperledger Fabric solutions In Detail Blockchain and Hyperledger technologies are hot topics. Hyperledger Fabric and Hyperledger Composer are open source projects that help organizations create private, permissioned blockchain networks. Applications that exploit them include finance, banking, supply chains, IoT, and much more. This book will be an easy reference to explore and build blockchain networks using Hyperledger technologies. This book will start by explaining the blockchain evolution, including an overview of relevant blockchain technologies. You will learn how to configure Hyperledger Fabric on a cloud platform. Understand the architectural components of Hyperledger Fabric, and how they are configured to build private blockchain networks, and applications that connect to them. You'll build up a network and application from scratch, starting with first principles. You'll learn how to implement smart contracts in chaincode and much more on the Hyperledger network. By the end of this book, you will be able to build and deploy your own decentralized applications using Hyperledger, addressing the key pain points encountered in the blockchain life cycle. Style and approach An easy-to-follow step by step guide which will help you get to grips with real world application of Hyperledger

Exploit design, deployment, and management of large-scale containers About This Book ? Explore the latest features available in Kubernetes 1.10 ? Ensure that your clusters are always available, scalable, and up to date ? Master the skills of designing and deploying large clusters on various cloud platforms Who This Book Is For Mastering Kubernetes is for you if you are a system administrator or a developer who has an intermediate understanding of Kubernetes and wish to master its advanced features. Basic knowledge of networking would also be helpful. In all, this advanced-level book provides a smooth pathway to mastering Kubernetes. What You Will Learn ? Architect a robust Kubernetes cluster for long-time operation ? Discover the advantages of running Kubernetes on GCE, AWS, Azure, and bare metal ? Understand the identity model of Kubernetes, along with the options for cluster federation ? Monitor and troubleshoot Kubernetes clusters and run a highly available Kubernetes ? Create and configure custom Kubernetes resources and use third-party resources in your automation workflows ? Enjoy the art of running complex stateful applications in your container environment ? Deliver applications as standard packages In Detail Kubernetes is an open source system that is used to automate the deployment, scaling, and management of containerized applications. If you are running more containers or want automated management of your containers, you need Kubernetes at your disposal. To put things into perspective, Mastering Kubernetes walks you through the advanced management of Kubernetes clusters. To start with, you will learn the fundamentals of both Kubernetes architecture and Kubernetes design in detail. You will discover how to run complex stateful microservices on Kubernetes including advanced features such as horizontal pod autoscaling, rolling updates, resource quotas, and persistent storage backend. Using real-world use cases, you will explore the options for network configuration, and understand how to set up, operate, and troubleshoot various Kubernetes networking plugins. In addition to this, you will get to grips with custom resource development and utilization in automation and maintenance workflows. To scale up your knowledge of Kubernetes, you will encounter some additional concepts based on the Kubernetes 1.10 release, such as Promethus, Role-based access control, API aggregation, and more. By the end of this book, you’ll know everything you need to graduate from intermediate to advanced level of understanding Kubernetes. Style and approach Delving into the design of the Kubernetes platform, the reader will be exposed to Kubernetes advanced features and best practices. This advanced-level book will provide a pathway to mastering Kubernetes.

Over 79 hands-on recipes for professional embedded Linux developers to optimize and boost their Yocto Project know-how About This Book ? Optimize your Yocto setup to speed up development and debug build issues ? Use what is quickly becoming the standard embedded Linux product builder framework—the Yocto Project ? Recipe-based implementation of best practices to optimize your Linux system Who This Book Is For If you are an embedded Linux developer with the basic knowledge of Yocto Project, this book is an ideal way to broaden your knowledge with recipes for embedded development. What You Will Learn ? Optimize your Yocto Project setup to speed up development and debug build issues ? Use Docker containers to build Yocto Project-based systems ? Take advantage of the user-friendly Toaster web interface to the Yocto Project build system ? Build and debug the Linux kernel and its device trees ? Customize your root filesystem with already-supported and new Yocto packages ? Optimize your production systems by reducing the size of both the Linux kernel and root filesystems ? Explore the mechanisms to increase the root filesystem security ? Understand the open source licensing requirements and how to comply with them when cohabiting with proprietary programs ? Create recipes, and build and run applications in C, C++, Python, Node.js, and Java In Detail The Yocto Project has become the de facto distribution build framework for reliable and robust embedded systems with a reduced time to market. You'll get started by working on a build system where you set up Yocto, create a build directory, and learn how to debug it. Then, you'll explore everything about the BSP layer, from creating a custom layer to debugging device tree issues. In addition to this, you’ll learn how to add a new software layer, packages, data, *s, and configuration files to your system. You will then cover topics based on application development, such as using the Software Development Kit and how to use the Yocto project in various development environments. Toward the end, you will learn how to debug, trace, and profile a running system. This second edition has been updated to include new content based on the latest Yocto release. Style and approach This recipe-based book will guide you through all the development stages of an embedded Linux product design using the Yocto Project.

Discover Golang's GUI libraries such as Go-GTK (GIMP Toolkit) and Go-Qt and build beautiful, performant, and responsive graphical applications Key Features * Conceptualize and build state-of-art GUI applications with Golang (Go) * Tackle the complexity of varying GUI application sizes with a structured and scalable approach * Get hands-on experience of GUI development with Shiny, and labs/ui, Fyne, and Walk Book Description Go is often compared to C++ when it comes to low-level programming and implementations that require faster processing, such as Graphical User Interfaces (GUIs). In fact, many claim that Go is superior to C++ in terms of its concurrency and ease of use. Most graphical application toolkits, though, are still written using C or C++, and so they don't enjoy the benefits of using a modern programming language such as Go. This guide to programming GUIs with Go 1.11 explores the various toolkits available, including UI, Walk, Shiny, and Fyne. The book compares the vision behind each project to help you pick the right approach for your project. Each framework is described in detail, outlining how you can build performant applications that users will love. To aid you further in creating applications using these emerging technologies, you'll be able to easily refer to code samples and screenshots featured in the book. In addition to toolkit-specific discussions, you'll cover more complex topics, such as how to structure growing graphical applications, and how cross-platform applications can integrate with each desktop operating system to create a seamless user experience. By delving into techniques and best practices for organizing and scaling Go-based graphical applications, you'll also glimpse Go's impressive concurrency system. In the concluding chapters, you'll discover how to distribute to the main desktop marketplaces and distribution channels. By the end of this book, you'll be a confident GUI developer who can use the Go language to boost the performance of your applications. What you will learn * Understand the benefits and complexities of building native graphical applications * Gain insights into how Go makes cross-platform graphical application development simple * Build platform-native GUI applications using andlabs/ui * Develop graphical Windows applications using Walk * Create multiplatform GUI applications using Shiny, Nuklear, and Fyne * Use Go wrappers for GTK and Qt for GUI application development * Streamline your requirements to pick the correct toolkit strategy Who this book is for This book is designed for Go developers who are interested in building native graphical applications for desktop computers and beyond. Some knowledge of building applications using Go is useful, but not essential. Experience in developing GUIs is not required as the book explores the benefits and challenges they pose. This book will also be beneficial for GUI application developers who are interested in trying Go.

Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality. Key Features * Develop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4)and Python * Apply machine learning and deep learning techniques with TensorFlow, Keras, and PyTorch * Discover the modern design patterns you should avoid when developing efficient computer vision applications Book Description OpenCV is considered to be one of the best open source computer vision and machine learning software libraries. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language. In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras. By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands. What you will learn * Handle files and images, and explore various image processing techniques * Explore image transformations, including translation, resizing, and cropping * Gain insights into building histograms * Brush up on contour detection, filtering, and drawing * Work with Augmented Reality to build marker-based and markerless applications * Work with the main machine learning algorithms in OpenCV * Explore the deep learning Python libraries and OpenCV deep learning capabilities * Create computer vision and deep learning web applications Who this book is for This book is designed for computer vision developers, engineers, and researchers who want to develop modern computer vision applications. Basic experience of OpenCV and Python programming is a must.

Bayesian modeling with PyMC3 and exploratory analysis of Bayesian models with ArviZ Key Features *A step-by-step guide to conduct Bayesian data analyses using PyMC3 and ArviZ *A modern, practical and computational approach to Bayesian statistical modeling *A tutorial for Bayesian analysis and best practices with the help of sample problems and practice exercises. Book Description The second edition of Bayesian Analysis with Python is an introduction to the main concepts of applied Bayesian inference and its practical implementation in Python using PyMC3, a state-of-the-art probabilistic programming library, and ArviZ, a new library for exploratory analysis of Bayesian models. The main concepts of Bayesian statistics are covered using a practical and computational approach. Synthetic and real data sets are used to introduce several types of models, such as generalized linear models for regression and classification, mixture models, hierarchical models, and Gaussian processes, among others. By the end of the book, you will have a working knowledge of probabilistic modeling and you will be able to design and implement Bayesian models for your own data science problems. After reading the book you will be better prepared to delve into more advanced material or specialized statistical modeling if you need to. What you will learn *Build probabilistic models using the Python library PyMC3 *Analyze probabilistic models with the help of ArviZ *Acquire the skills required to sanity check models and modify them if necessary *Understand the advantages and caveats of hierarchical models *Find out how different models can be used to answer different data analysis questions *Compare models and choose between alternative ones *Discover how different models are unified from a probabilistic perspective *Think probabilistically and benefit from the flexibility of the Bayesian framework Who this book is for If you are a student, data scientist, researcher, or a developer looking to get started with Bayesian data analysis and probabilistic programming, this book is for you. The book is introductory so no previous statistical knowledge is required, although some experience in using Python and NumPy is expected.

Learn how to write scalable and concurrent programs in Scala, a language that grows with you. About This Book ? Get a grip on the functional features of the Scala programming language ? Understand and develop optimal applications using object-oriented and functional Scala constructs ? Learn reactive principles with Scala and work with the Akka framework Who This Book Is For This book is for programmers who choose to get a grip over Scala to write concurrent, scalable, and reactive programs. No prior experience with any programming language is required to learn the concepts explained in this book. Knowledge of any programming language would help the reader understanding concepts faster though. What You Will Learn ? Get to know the reasons for choosing Scala: its use and the advantages it provides over other languages ? Bring together functional and object-oriented programming constructs to make a manageable application ? Master basic to advanced Scala constructs ? Test your applications using advanced testing methodologies such as TDD ? Select preferred language constructs from the wide variety of constructs provided by Scala ? Make the transition from the object-oriented paradigm to the functional programming paradigm ? Write clean, concise, and powerful code with a functional mindset ? Create concurrent, scalable, and reactive applications utilizing the advantages of Scala In Detail Scala is a general-purpose programming language that supports both functional and object-oriented programming paradigms. Due to its concise design and versatility, Scala's applications have been extended to a wide variety of fields such as data science and cluster computing. You will learn to write highly scalable, concurrent, and testable programs to meet everyday software requirements. We will begin by understanding the language basics, syntax, core data types, literals, variables, and more. From here you will be introduced to data structures with Scala and you will learn to work with higher-order functions. Scala's powerful collections framework will help you get the best out of immutable data structures and utilize them effectively. You will then be introduced to concepts such as pattern matching, case classes, and functional programming features. From here, you will learn to work with Scala's object-oriented features. Going forward, you will learn about asynchronous and reactive programming with Scala, where you will be introduced to the Akka framework. Finally, you will learn the interoperability of Scala and Java. After reading this book, you'll be well versed with this language and its features, and you will be able to write scalable, concurrent, and reactive programs in Scala. Style and approach This book is for programmers who want to master Scala to write concurrent, scalable, and reactive programs. Though no experience with any programming language is needed, some basic knowledge would help understand concepts faster.

Build fast, scalable, and high performing applications with Delphi About This Book ? Build efficient and concurrent applications in Delphi with focused examples ? Identify performance bottlenecks and apply the correct algorithm to increase the performance of applications. ? Delve into parallel programming and memory management to optimize your code Who This Book Is For This book is for Delphi developers who would like to build high performance applications with Delphi. Prior knowledge of Delphi is assumed. What You Will Learn ? Find performance bottlenecks and easily mitigate them ? Discover different approaches to fix algorithms ? Understand parallel programming and work with various tools included with Delphi ? Master the RTL for code optimization ? Explore memory managers and their implementation ? Leverage external libraries to write better performing programs In Detail Delphi is a cross-platform Integrated Development Environment (IDE) that supports rapid application development for Microsoft Windows, Apple Mac OS X, Google Android, iOS, and now Linux with RAD Studio 10.2. This book will be your guide to build efficient high performance applications with Delphi. The book begins by explaining how to find performance bottlenecks and apply the correct algorithm to fix them. It will teach you how to improve your algorithms before taking you through parallel programming. You’ll then explore various tools to build highly concurrent applications. After that, you’ll delve into improving the performance of your code and master cross-platform RTL improvements. Finally, we’ll go through memory management with Delphi and you’ll see how to leverage several external libraries to write better performing programs. By the end of the book, you’ll have the knowledge to create high performance applications with Delphi. Style and approach This book will take a step-by-step approach with focused examples to teach you how to increase the performance of applications.

Take your application development skills to the next level by implementing Spring Boot features effectively About This Book ? This collection of effective recipes serves as guidelines for Spring Boot application development ? Get up to date with features of the latest version of Spring Boot 2.0 ? Tips and tricks to improve your efficiency through the stages of software development Who This Book Is For This book is for Java Developers who have good knowledge and understanding of Spring and Java application development. What You Will Learn ? Get to know Spring Boot Starters and create custom auto-configurations ? Work with custom annotations that enable bean activation ? Use DevTools to easily develop and debug applications ? Learn the effective testing techniques by integrating Cucumber and Spock ? Observe an eternal application configuration using Consul ? Move your existing Spring Boot applications to the cloud ? Use Hashicorp Consul and Netflix Eureka for dynamic Service Discovery ? Understand the various mechanisms that Spring Boot provides to examine an application’s health In Detail The Spring framework provides great flexibility for Java development, which also results in tedious configuration work. Spring Boot addresses the configuration difficulties of Spring and makes it easy to create standalone, production-grade Spring-based applications. This practical guide makes the existing development process more efficient. Spring Boot Cookbook 2.0 Second Edition smartly combines all the skills and expertise to efficiently develop, test, deploy, and monitor applications using Spring Boot on premise and in the cloud. We start with an overview of the important Spring Boot features you will learn to create a web application for a RESTful service. Learn to fine-tune the behavior of a web application by learning about custom routes and asset paths and how to modify routing patterns. Address the requirements of a complex enterprise application and cover the creation of custom Spring Boot starters. This book also includes examples of the new and improved facilities available to create various kinds of tests introduced in Spring Boot 1.4 and 2.0, and gain insights into Spring Boot DevTools. Explore the basics of Spring Boot Cloud modules and various Cloud starters to make applications in “Cloud Native” and take advantage of Service Discovery and Circuit Breakers. Style and approach This practical guide follows a recipe-based approach and provides extremely helpful guidelines to build, configure, and customize your Spring Boot applications.

Get command of your organizational Big Data using the power of data science and analytics About This Book ? A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions ? Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses ? Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Who This Book Is For The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience. What You Will Learn ? Get a 360-degree view into the world of Big Data, data science and machine learning ? Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives ? Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R ? Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions ? Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications ? Understand corporate strategies for successful Big Data and data science projects ? Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies In Detail Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book. Style and approach This book equips you with a knowledge of various NoSQL tools, R, Python programming, cloud platforms, and techniques so you can use them to store, analyze, and deliver meaningful insights from your data.

Learn the techniques for object recognition, 3D reconstruction, stereo imaging, and other computer vision applications using examples on different functions of OpenCV. About This Book ? Learn how to apply complex visual effects to images with OpenCV 3.x and Python ? Extract features from an image and use them to develop advanced applications ? Build algorithms to help you understand image content and perform visual searches ? Get to grips with advanced techniques in OpenCV such as machine learning, artificial neural network, 3D reconstruction, and augmented reality Who This Book Is For This book is intended for Python developers who are new to OpenCV and want to develop computer vision applications with OpenCV and Python. This book is also useful for generic software developers who want to deploy computer vision applications on the cloud. It would be helpful to have some familiarity with basic mathematical concepts such as vectors, matrices, and so on. What You Will Learn ? Detect shapes and edges from images and videos ? How to apply filters on images and videos ? Use different techniques to manipulate and improve images ? Extract and manipulate particular parts of images and videos ? Track objects or colors from videos ? Recognize specific object or faces from images and videos ? How to create Augmented Reality applications ? Apply artificial neural networks and machine learning to improve object recognition In Detail Computer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we have more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. Focusing on OpenCV 3.x and Python 3.6, this book will walk you through all the building blocks needed to build amazing computer vision applications with ease. We start off by manipulating images using simple filtering and geometric transformations. We then discuss affine and projective transformations and see how we can use them to apply cool advanced manipulations to your photos like resizing them while keeping the content intact or smoothly removing undesired elements. We will then cover techniques of object tracking, body part recognition, and object recognition using advanced techniques of machine learning such as artificial neural network. 3D reconstruction and augmented reality techniques are also included. The book covers popular OpenCV libraries with the help of examples. This book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation. By the end of this book, you will have acquired the skills to use OpenCV and Python to develop real-world computer vision applications. Style and approach The book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation.