Your one-stop guide to learning and implementing artificial neural networks with Keras effectively Key Features * Design and create neural network architectures on different domains using Keras * Integrate neural network models in your applications using this highly practical guide * Get ready for the future of neural networks through transfer learning and predicting multi network models Book Description Neural networks are used to solve a wide range of problems in different areas of AI and deep learning. Hands-On Neural Networks with Keras will start with teaching you about the core concepts of neural networks. You will delve into combining different neural network models and work with real-world use cases, including computer vision, natural language understanding, synthetic data generation, and many more. Moving on, you will become well versed with convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM) networks, autoencoders, and generative adversarial networks (GANs) using real-world training datasets. We will examine how to use CNNs for image recognition, how to use reinforcement learning agents, and many more. We will dive into the specific architectures of various networks and then implement each of them in a hands-on manner using industry-grade frameworks. By the end of this book, you will be highly familiar with all prominent deep learning models and frameworks, and the options you have when applying deep learning to real-world scenarios and embedding artificial intelligence as the core fabric of your organization. What you will learn * Understand the fundamental nature and workflow of predictive data modeling * Explore how different types of visual and linguistic signals are processed by neural networks * Dive into the mathematical and statistical ideas behind how networks learn from data * Design and implement various neural networks such as CNNs, LSTMs, and GANs * Use different architectures to tackle cognitive tasks and embed intelligence in systems * Learn how to generate synthetic data and use augmentation strategies to improve your models * Stay on top of the latest academic and commercial developments in the field of AI Who this book is for This book is for machine learning practitioners, deep learning researchers and AI enthusiasts who are looking to get well versed with different neural network architecture using Keras. Working knowledge of Python programming language is mandatory.

Write efficient, reusable scripts to build custom characters, game environments, and control enemy AI Key Features * Build captivating multiplayer games using Unreal Engine and C++ * Incorporate existing C++ libraries into your game to add extra functionality such as hardware integration * Practical solutions for memory management, error handling, inputs, and collision for your game codebase Book Description Unreal Engine 4 (UE4) is a popular and award-winning game engine that powers some of the most popular games. A truly powerful tool for game development, there has never been a better time to use it for both commercial and independent projects. With more than 100 recipes, this book shows how to unleash the power of C++ while developing games with Unreal Engine. This book takes you on a journey to jumpstart your C++ and UE4 development skills. You will start off by setting up UE4 for C++ development and learn how to work with Visual Studio, a popular code editor. You will learn how to create C++ classes and structs the Unreal way. This will be followed by exploring memory management, smart pointers, and debugging your code. You will then learn how to make your own Actors and Components through code and how to handle input and collision events. You will also get exposure to many elements of game development including creating user interfaces, artificial intelligence, and writing code with networked play in mind. You will also learn how to add on to the Unreal Editor itself. With a range of task-oriented recipes, this book provides actionable information about writing code for games with UE4 using C++. By the end of the book, you will be empowered to become a top-notch developer with UE4 using C++ as your scripting language! What you will learn * Create C++ classes and structs that integrate well with UE4 and the Blueprints editor * Discover how to work with various APIs that Unreal Engine already contains * Utilize advanced concepts such as events, delegates, and interfaces in your UE4 projects * Build user interfaces using Canvas and UMG through C++ * Extend the Unreal Editor by creating custom windows and editors * Implement AI tasks and services using C++, Blackboard, and Behavior Trees * Write C++ code with networking in mind and replicate properties and functions Who this book is for If you are really passionate game developer looking for solutions to common scripting problems, then this is the book for you. Understanding of the fundamentals of game design and C++ is expected to get the most from this book.

Create a real-world application in Go and explore various frameworks and methodologies for full-stack development Key Features * Organize your isomorphic codebase to enhance the maintainability of your application * Build web APIs and middleware in the Go language by making use of the popular Gin framework * Implement real-time web application functionality with WebSockets Book Description The Go programming language has been rapidly adopted by developers for building web applications. With its impressive performance and ease of development, Go enjoys the support of a wide variety of open source frameworks, for building scalable and high-performant web services and apps. Hands-On Full Stack Development with Go is a comprehensive guide that covers all aspects of full stack development with Go. This clearly written, example-rich book begins with a practical exposure to Go development and moves on to build a frontend with the popular React framework. From there, you will build RESTful web APIs utilizing the Gin framework. After that, we will dive deeper into important software backend concepts, such as connecting to the database via an ORM, designing routes for your services, securing your services, and even charging credit cards via the popular Stripe API. We will also cover how to test, and benchmark your applications efficiently in a production environment. In the concluding chapters, we will cover isomorphic developments in pure Go by learning about GopherJS. As you progress through the book, you'll gradually build a musical instrument online store application from scratch. By the end of the book, you will be confident in taking on full stack web applications in Go. What you will learn * Understand Go programming by building a real-world application * Learn the React framework to develop a frontend for your application * Understand isomorphic web development utilizing the GopherJS framework * Explore methods to write RESTful web APIs in Go using the Gin framework * Learn practical topics such as ORM layers, secure communications, and Stripe's API * Learn methods to benchmark and test web APIs in Go Who this book is for Hands-On Full Stack Development with Go will appeal to developers who are looking to start building amazing full stack web applications in Go. Basic knowhow of Go language and JavaScript is expected. The book targets web developers who are looking to move to the Go language.

Learn how to build complete machine learning systems with IBM Cloud and Watson Machine learning services Key Features * Implement data science and machine learning techniques to draw insights from real-world data * Understand what IBM Cloud platform can help you to implement cognitive insights within applications * Understand the role of data representation and feature extraction in any machine learning system Book Description IBM Cloud is a collection of cloud computing services for data analytics using machine learning and artificial intelligence (AI). This book is a complete guide to help you become well versed with machine learning on the IBM Cloud using Python. Hands-On Machine Learning with IBM Watson starts with supervised and unsupervised machine learning concepts, in addition to providing you with an overview of IBM Cloud and Watson Machine Learning. You'll gain insights into running various techniques, such as K-means clustering, K-nearest neighbor (KNN), and time series prediction in IBM Cloud with real-world examples. The book will then help you delve into creating a Spark pipeline in Watson Studio. You will also be guided through deep learning and neural network principles on the IBM Cloud using TensorFlow. With the help of NLP techniques, you can then brush up on building a chatbot. In later chapters, you will cover three powerful case studies, including the facial expression classification platform, the automated classification of lithofacies, and the multi-biometric identity authentication platform, helping you to become well versed with these methodologies. By the end of this book, you will be ready to build efficient machine learning solutions on the IBM Cloud and draw insights from the data at hand using real-world examples. What you will learn * Understand key characteristics of IBM machine learning services * Run supervised and unsupervised techniques in the cloud * Understand how to create a Spark pipeline in Watson Studio * Implement deep learning and neural networks on the IBM Cloud with TensorFlow * Create a complete, cloud-based facial expression classification solution * Use biometric traits to build a cloud-based human identification system Who this book is for This beginner-level book is for data scientists and machine learning engineers who want to get started with IBM Cloud and its machine learning services using practical examples. Basic knowledge of Python and some understanding of machine learning will be useful.

Your one stop guide to automating infrastructure security using DevOps and DevSecOps Key Features * Secure and automate techniques to protect web, mobile or cloud services * Automate secure code inspection in C++, Java, Python, and JavaScript * Integrate security testing with automation frameworks like fuzz, BDD, Selenium and Robot Framework Book Description Security automation is the automatic handling of software security assessments tasks. This book helps you to build your security automation framework to scan for vulnerabilities without human intervention. This book will teach you to adopt security automation techniques to continuously improve your entire software development and security testing. You will learn to use open source tools and techniques to integrate security testing tools directly into your CI/CD framework. With this book, you will see how to implement security inspection at every layer, such as secure code inspection, fuzz testing, Rest API, privacy, infrastructure security, and web UI testing. With the help of practical examples, this book will teach you to implement the combination of automation and Security in DevOps. You will learn about the integration of security testing results for an overall security status for projects. By the end of this book, you will be confident implementing automation security in all layers of your software development stages and will be able to build your own in-house security automation platform throughout your mobile and cloud releases. What you will learn * Automate secure code inspection with open source tools and effective secure code scanning suggestions * Apply security testing tools and automation frameworks to identify security vulnerabilities in web, mobile and cloud services * Integrate security testing tools such as OWASP ZAP, NMAP, SSLyze, SQLMap, and OpenSCAP * Implement automation testing techniques with Selenium, JMeter, Robot Framework, Gauntlt, BDD, DDT, and Python unittest * Execute security testing of a Rest API Implement web application security with open source tools and script templates for CI/CD integration * Integrate various types of security testing tool results from a single project into one dashboard Who this book is for The book is for software developers, architects, testers and QA engineers who are looking to leverage automated security testing techniques.

Build your Machine Learning portfolio by creating 6 cutting-edge Artificial Intelligence projects using neural networks in Python Key Features * Discover neural network architectures (like CNN and LSTM) that are driving recent advancements in AI * Build expert neural networks in Python using popular libraries such as Keras * Includes projects such as object detection, face identification, sentiment analysis, and more Book Description Neural networks are at the core of recent AI advances, providing some of the best resolutions to many real-world problems, including image recognition, medical diagnosis, text analysis, and more. This book goes through some basic neural network and deep learning concepts, as well as some popular libraries in Python for implementing them. It contains practical demonstrations of neural networks in domains such as fare prediction, image classification, sentiment analysis, and more. In each case, the book provides a problem statement, the specific neural network architecture required to tackle that problem, the reasoning behind the algorithm used, and the associated Python code to implement the solution from scratch. In the process, you will gain hands-on experience with using popular Python libraries such as Keras to build and train your own neural networks from scratch. By the end of this book, you will have mastered the different neural network architectures and created cutting-edge AI projects in Python that will immediately strengthen your machine learning portfolio. What you will learn * Learn various neural network architectures and its advancements in AI * Master deep learning in Python by building and training neural network * Master neural networks for regression and classification * Discover convolutional neural networks for image recognition * Learn sentiment analysis on textual data using Long Short-Term Memory * Build and train a highly accurate facial recognition security system Who this book is for This book is a perfect match for data scientists, machine learning engineers, and deep learning enthusiasts who wish to create practical neural network projects in Python. Readers should already have some basic knowledge of machine learning and neural networks.

Enhance your programming skills by learning the intricacies of object oriented programming in C# 8 Key Features * Understand the four pillars of OOP; encapsulation, inheritance, abstraction and polymorphism * Leverage the latest features of C# 8 including nullable reference types and Async Streams * Explore various design patterns, principles, and best practices in OOP Book Description Object-oriented programming (OOP) is a programming paradigm organized around objects rather than actions, and data rather than logic. With the latest release of C#, you can look forward to new additions that improve object-oriented programming. This book will get you up to speed with OOP in C# in an engaging and interactive way. The book starts off by introducing you to C# language essentials and explaining OOP concepts through simple programs. You will then go on to learn how to use classes, interfacesm and properties to write pure OOP code in your applications. You will broaden your understanding of OOP further as you delve into some of the advanced features of the language, such as using events, delegates, and generics. Next, you will learn the secrets of writing good code by following design patterns and design principles. You'll also understand problem statements with their solutions and learn how to work with databases with the help of ADO.NET. Further on, you'll discover a chapter dedicated to the Git version control system. As you approach the conclusion, you'll be able to work through OOP-specific interview questions and understand how to tackle them. By the end of this book, you will have a good understanding of OOP with C# and be able to take your skills to the next level. What you will learn * Master OOP paradigm fundamentals * Explore various types of exceptions * Utilize C# language constructs efficiently * Solve complex design problems by understanding OOP * Understand how to work with databases using ADO.NET * Understand the power of generics in C# * Get insights into the popular version control system, Git * Learn how to model and design your software Who this book is for This book is designed for people who are new to object-oriented programming. Basic C# skills are assumed, however, prior knowledge of OOP in any other language is not required.

Gain basic skills in network forensics and learn how to apply them effectively Key Features * Investigate network threats with ease * Practice forensics tasks such as intrusion detection, network analysis, and scanning * Learn forensics investigation at the network level Book Description Network forensics is a subset of digital forensics that deals with network attacks and their investigation. In the era of network attacks and malware threat, it’s now more important than ever to have skills to investigate network attacks and vulnerabilities. Hands-On Network Forensics starts with the core concepts within network forensics, including coding, networking, forensics tools, and methodologies for forensic investigations. You’ll then explore the tools used for network forensics, followed by understanding how to apply those tools to a PCAP file and write the accompanying report. In addition to this, you will understand how statistical flow analysis, network enumeration, tunneling and encryption, and malware detection can be used to investigate your network. Towards the end of this book, you will discover how network correlation works and how to bring all the information from different types of network devices together. By the end of this book, you will have gained hands-on experience of performing forensics analysis tasks. What you will learn * Discover and interpret encrypted traffic * Learn about various protocols * Understand the malware language over wire * Gain insights into the most widely used malware * Correlate data collected from attacks * Develop tools and custom scripts for network forensics automation Who this book is for The book targets incident responders, network engineers, analysts, forensic engineers and network administrators who want to extend their knowledge from the surface to the deep levels of understanding the science behind network protocols, critical indicators in an incident and conducting a forensic search over the wire.

Go beyond the basics and unleash the full power of QGIS 3.4 and 3.6 with practical, step-by-step examples Key Features * One-stop solution to all of your GIS needs * Master QGIS by learning about database integration, and geoprocessing tools * Learn about the new and updated Processing toolbox and perform spatial analysis Book Description QGIS is an open source solution to GIS and widely used by GIS professionals all over the world. It is the leading alternative to proprietary GIS software. Although QGIS is described as intuitive, it is also, by default, complex. Knowing which tools to use and how to apply them is essential to producing valuable deliverables on time. Starting with a refresher on the QGIS basics and getting you acquainted with the latest QGIS 3.6 updates, this book will take you all the way through to teaching you how to create a spatial database and a GeoPackage. Next, you will learn how to style raster and vector data by choosing and managing different colors. The book will then focus on processing raster and vector data. You will be then taught advanced applications, such as creating and editing vector data. Along with that, you will also learn about the newly updated Processing Toolbox, which will help you develop the advanced data visualizations. The book will then explain to you the graphic modeler, how to create QGIS plugins with PyQGIS, and how to integrate Python analysis scripts with QGIS. By the end of the book, you will understand how to work with all aspects of QGIS and will be ready to use it for any type of GIS work. What you will learn * Create and manage a spatial database * Get to know advanced techniques to style GIS data * Prepare both vector and raster data for processing * Add heat maps, live layer effects, and labels to your maps * Master LAStools and GRASS integration with the Processing Toolbox * Edit and repair topological data errors * Automate workflows with batch processing and the QGIS Graphical Modeler * Integrate Python scripting into your data processing workflows * Develop your own QGIS plugins Who this book is for If you are a GIS professional, a consultant, a student, or perhaps a fast learner who wants to go beyond the basics of QGIS, then this book is for you. It will prepare you to realize the full potential of QGIS.

Solve real-world data problems with R and machine learning Key Features * Third edition of the bestselling, widely acclaimed R machine learning book, updated and improved for R 3.5 and beyond * Harness the power of R to build flexible, effective, and transparent machine learning models * Learn quickly with a clear, hands-on guide by experienced machine learning teacher and practitioner, Brett Lantz Book Description Machine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data. Machine Learning with R, Third Edition provides a hands-on, readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to uncover key insights, make new predictions, and visualize your findings. This new 3rd edition updates the classic R data science book with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning. Find powerful new insights in your data; discover machine learning with R. What you will learn * Discover the origins of machine learning and how exactly a computer learns by example * Prepare your data for machine learning work with the R programming language * Classify important outcomes using nearest neighbor and Bayesian methods * Predict future events using decision trees, rules, and support vector machines * Forecast numeric data and estimate financial values using regression methods * Model complex processes with artificial neural networks — the basis of deep learning * Avoid bias in machine learning models * Evaluate your models and improve their performance * Connect R to SQL databases and emerging big data technologies such as Spark, H2O, and TensorFlow Who this book is for Data scientists, students, and other practitioners who want a clear, accessible guide to machine learning with R.

Implement defensive techniques in your ecosystem successfully with Python Key Features * Identify and expose vulnerabilities in your infrastructure with Python * Learn custom exploit development . * Make robust and powerful cybersecurity tools with Python Book Description With the current technological and infrastructural shift, penetration testing is no longer a process-oriented activity. Modern-day penetration testing demands lots of automation and innovation; the only language that dominates all its peers is Python. Given the huge number of tools written in Python, and its popularity in the penetration testing space, this language has always been the first choice for penetration testers. Hands-On Penetration Testing with Python walks you through advanced Python programming constructs. Once you are familiar with the core concepts, you’ll explore the advanced uses of Python in the domain of penetration testing and optimization. You’ll then move on to understanding how Python, data science, and the cybersecurity ecosystem communicate with one another. In the concluding chapters, you’ll study exploit development, reverse engineering, and cybersecurity use cases that can be automated with Python. By the end of this book, you’ll have acquired adequate skills to leverage Python as a helpful tool to pentest and secure infrastructure, while also creating your own custom exploits. What you will learn * Get to grips with Custom vulnerability scanner development * Familiarize yourself with web application scanning automation and exploit development * Walk through day-to-day cybersecurity scenarios that can be automated with Python * Discover enterprise-or organization-specific use cases and threat-hunting automation * Understand reverse engineering, fuzzing, buffer overflows , key-logger development, and exploit development for buffer overflows. * Understand web scraping in Python and use it for processing web responses * Explore Security Operations Centre (SOC) use cases * Get to understand Data Science, Python, and cybersecurity all under one hood Who this book is for If you are a security consultant , developer or a cyber security enthusiast with little or no knowledge of Python and want in-depth insight into how the pen-testing ecosystem and python combine to create offensive tools , exploits , automate cyber security use-cases and much more then this book is for you. Hands-On Penetration Testing with Python guides you through the advanced uses of Python for cybersecurity and pen-testing, helping you to better understand security loopholes within your infrastructure .

Get ready for the Windows 10: 70-698 exam and configure Windows to manage data recovery Key Features * Implement Windows 10 operational and administrative tasks * Configure devices, remote management settings, advanced management tools, and device drivers * Comprehensive guide to help you work efficiently in Windows 10 Book Description The Installing and Configuring Windows 10: 70-698 Exam Guide is designed to confirm what you already know, while also updating your knowledge of Windows 10. With its easy-to-follow guidance, you will quickly learn the user interface and discover steps to work efficiently in Windows 10 to rule out delays and obstacles. This book begins by covering various ways of installing Windows 10, followed by instructions on post-installation tasks. You will learn about the deployment of Windows 10 in Enterprise and also see how to configure networking in Windows 10. You’ll understand how to leverage Disk Management and Windows PowerShell to configure disks, volumes, and file system options. As you progress through the chapters, you will be able to set up remote management in Windows 10 and learn more about Windows update usage, behavior, and settings. You will also gain insights that will help you monitor and manage data recovery and explore how to configure authentication, authorization, and advanced management tools in Windows 10. By the end of this book, you will be equipped with enough knowledge to take the 70-698 exam and explore different study methods to improve your chances of passing the exam with ease. What you will learn * Discover various ways of installing Windows 10 * Understand how to configure devices and device drivers * Configure and support IPv4 and IPv6 network settings * Troubleshoot storage and removable device issues * Get to grips with data access and usage * Explore the advanced management tools available in Windows 10 Who this book is for This book is for IT professionals who perform installation, configuration, general local management and maintenance of Windows 10 core services and are preparing to clear the Windows 10: 70-698 exam

Implement machine learning and deep learning methodologies to build smart, cognitive AI projects using Python Key Features * A go-to guide to help you master AI algorithms and concepts * 8 real-world projects tackling different challenges in healthcare, e-commerce, and surveillance * Use TensorFlow, Keras, and other Python libraries to implement smart AI applications Book Description This book will be a perfect companion if you want to build insightful projects from leading AI domains using Python. The book covers detailed implementation of projects from all the core disciplines of AI. We start by covering the basics of how to create smart systems using machine learning and deep learning techniques. You will assimilate various neural network architectures such as CNN, RNN, LSTM, to solve critical new world challenges. You will learn to train a model to detect diabetic retinopathy conditions in the human eye and create an intelligent system for performing a video-to-text translation. You will use the transfer learning technique in the healthcare domain and implement style transfer using GANs. Later you will learn to build AI-based recommendation systems, a mobile app for sentiment analysis and a powerful chatbot for carrying customer services. You will implement AI techniques in the cybersecurity domain to generate Captchas. Later you will train and build autonomous vehicles to self-drive using reinforcement learning. You will be using libraries from the Python ecosystem such as TensorFlow, Keras and more to bring the core aspects of machine learning, deep learning, and AI. By the end of this book, you will be skilled to build your own smart models for tackling any kind of AI problems without any hassle. What you will learn * Build an intelligent machine translation system using seq-2-seq neural translation machines * Create AI applications using GAN and deploy smart mobile apps using TensorFlow * Translate videos into text using CNN and RNN * Implement smart AI Chatbots, and integrate and extend them in several domains * Create smart reinforcement, learning-based applications using Q-Learning * Break and generate CAPTCHA using Deep Learning and Adversarial Learning Who this book is for This book is intended for data scientists, machine learning professionals, and deep learning practitioners who are ready to extend their knowledge and potential in AI. If you want to build real-life smart systems to play a crucial role in every complex domain, then this book is what you need. Knowledge of Python programming and a familiarity with basic machine learning and deep learning concepts are expected to help you get the most out of the book

Harness the power of React Native to build 4 real-world apps About This Book ? Build quirky and fun projects from scratch and become efficient with React Native ? Learn to build professional Android and iOS applications using your existing JavaScript knowledge ? Use isomorphic principles to build mobile apps that offer a native user experience ? Embedded with assessments that will help you revise the concepts you have learned in this course Who This Book Is For This book is for developers who want to build amazing cross-platform apps with React Native. What You Will Learn ? Structure React Native projects to ease maintenance and extensibility ? Optimize a project to speed up development ? Use external modules to speed up the development and maintenance of your projects ? Explore the different UI and code patterns to be used for iOS and Android ? Get to know the best practices when building apps in React Native In Detail React Native helps web and mobile developers to build cross-platform apps that perform at the same level as any other natively developed app. The range of apps that can be built using this library is huge. From e-commerce to games, React Native is a good fit for any mobile project due to its flexibility and extendable nature. This project-based book consists of four standalone projects. Each project will help you gain a sound understanding of the framework and build mobile apps with native user experience. Starting with a simple standalone car booking app, you will progressively move on to building advanced apps by adding connectivity with external APIs, using native features, such as the camera or microphone, in the mobile device, integrating with state management libraries such as Redux or MobX, or leveraging React Native’s performance by building a full-featured game. This book is ideal for developers who want to build amazing cross-platform apps with React Native. This book is embedded with useful assessments that will help you revise the concepts you have learned in this book. Style and approach This project-based book consists of four projects. Each project is a standalone project that covers the core techniques and concepts of React Native. Note: This book is a blend of text and quizzes, all packaged up keeping your journey in mind. It includes content from the following Packt products: ? React Native Blueprints by Emilio Rodriguez Martinez

Learn to build a high-performance functional prototype of a voting web application from scratch using Elixir and Phoenix About This Book ? Build a strong foundation in Functional-Programming techniques while learning to build compelling web applications ? Understand the Elixir Concurrency and parallelization model to build high-performing blazingly fast applications ? Learn to test, debug and deploy your web applications using Phoenix framework Who This Book Is For This book is for people with a basic knowledge of Elixir, who want to start building web applications. Prior experience with web technologies is assumed. What You Will Learn ? Learn Phoenix Framework fundamentals and v1.3's new application structure ? Build real-time applications with channels and presence ? Utilize GenServers and other OTP fundamentals to keep an application stable ? Track users as they sign in and out of chat with Phoenix’s built-in presence functionality ? Write your own database interaction code that is safe, bug-free, and easy to work with ? Explore testing and debugging methodologies to understand a real software development lifecycle for a Phoenix application ? Deploy and run your Phoenix application in production In Detail Phoenix is a modern web development framework that is used to build API’s and web applications. It is built on Elixir and runs on Erlang VM which makes it much faster than other options. With Elixir and Phoenix, you build your application the right way, ready to scale and ready for the increasing demands of real-time web applications. This book covers the basics of the Phoenix web framework, showing you how to build a community voting application, and is divided into three parts. In the first part, you will be introduced to Phoenix and Elixir and understand the core terminologies that are used to describe them. You will also learn to build controller pages, store and retrieve data, add users to your app pages and protect your database. In the second section you will be able to reinforce your knowledge of architecting real time applications in phoenix and not only debug these applications but also diagnose issues in them. In the third and final section you will have the complete understanding of deploying and running the phoenix application and should be comfortable to make your first application release By the end of this book, you'll have a strong grasp of all of the core fundamentals of the Phoenix framework, and will have built a full production-ready web application from scratch. Style and approach Covers the basics of the Phoenix web framework by building a complete real-time application and showing the new structure changes introduced in Phoenix v1.3

Manage on-premises and cloud IT assets from one console About This Book ? Empower yourself with practical recipes to collect and analyze operational insights on Windows and Linux servers in your on premises datacenters and in any public cloud environments such as Azure and AWS. ? Build capabilities through practical tasks and techniques to collect and analyze machine data ? Address business challenges and discover means to accommodate workloads and instances in a low cost manner Who This Book Is For This book is written for the IT professional and general reader who is interested in technology themes such as DevOps, Big Data Analytics, and digital transformation concepts. Azure and other cloud platform administrators, cloud professionals, and technology analysts who would like to solve everyday problems quickly and efficiently with hybrid management tools available in the Microsoft product ecosystem will derive much value from this book. Prior experience with OMS 2012 would be helpful. What You Will Learn ? Understand the important architectural considerations and strategies for OMS ? Use advanced search query commands and strategies to derive insights from indexed data ? Make use of alerting in OMS such as alert actions, and available options for the entire lifecycle of the alert ? Discover some practical tips for monitoring Azure container service containers and clusters using OMS ? Review and use the backup options available through the Azure backup service, as well as data recovery options available through Azure Site Recovery (ASR) ? Understand how to advance important DevOps concepts within your IT organization ? Learn how to manage configurations and automate process In Detail Microsoft Operations Management Suite Cookbook begins with an overview of how to hit the ground running with OMS insights and analytics. Next, you will learn to search and analyze data to retrieve actionable insights, review alert generation from the analyzed data, and use basic and advanced Log search queries in Azure Log Analytics. Following this, you will explore some other management solutions that provide functionality related to workload assessment, application dependency mapping, automation and configuration management, and security and compliance. You will also become well versed with the data protection and recovery functionalities of OMS Protection and Recovery, and learn how to use Azure Automation components and features in OMS. Finally you will learn how to evaluate key considerations for using the Security and Audit solution, and working with Security and Compliance in OMS. By the end of the book, you will be able to configure and utilize solution offerings in OMS, understand OMS workflows, how to unlock insights, integrate capabilities into new or existing workflows, manage configurations, and automate tasks and processes. Style and approach This is a recipe based guide where early chapters introduce the main concepts and key capabilities, and the later chapters delve into more advance concepts.

Develop and manage applications on the AWS and OpenStack platforms with this comprehensive learning guide. About This Book ? A step-by-step guide to help you develop applications on the hybrid cloud platform. ? Acquire an in-depth understanding of the OpenStack and AWS cloud platforms. ? Extensive source code examples for OpenStack and AWS applications. ? Easily troubleshoot OpenStack and AWS issues. ? Understand the best practices and security measures for the hybrid cloud platform. Who This Book Is For If you are an IT professional, developer, or a DevOps engineer looking to develop and manage your applications on the hybrid cloud platform, then this book is for you. Some prior knowledge of the public and private cloud will enhance your skills. Developers looking to build applications using AWS or OpenStack services will also benefit from this book. What You Will Learn ? Understand the hybrid cloud platform ? Explore the AWS and OpenStack cloud platforms in depth ? Develop AWS applications with source code examples ? Develop OpenStack applications with source code examples ? Troubleshoot OpenStack and AWS ? Learn hybrid cloud best practices ? Understand security measures on the hybrid cloud In Detail This book introduces you to the hybrid cloud platform, and focuses on the AWS public cloud and OpenStack private cloud platforms. It provides a deep dive into the AWS and OpenStack cloud platform services that are essential for developing hybrid cloud applications. You will learn to develop applications on AWS and OpenStack platforms with ease by leveraging various cloud services and taking advantage of PaaS. The book provides you with the ability to leverage the flexibility of choosing a cloud platform for migrating your existing resources to the cloud, as well as developing hybrid cloud applications that can migrate virtual machine instances from AWS to OpenStack and vice versa. You will also be able to build and test cloud applications without worrying about the system that your development environment supports. The book also provides an in-depth understanding of the best practices that are followed across the industry for developing cloud applications, as well as for adapting the hybrid cloud platform. Lastly, it also sheds light on various troubleshooting techniques for OpenStack and AWS cloud platform services that are consumed by hybrid cloud applications. By the end of this book, you will have a deep understanding of the hybrid cloud platform and will be able to develop robust, efficient, modular, scalable, and ?exible cloud applications. Style and approach This book follows a practical approach to become familiar with the AWS and OpenStack platform from a developer's perspective.

Work with Python and powerful open source tools such as Gensim and spaCy to perform modern text analysis, natural language processing, and computational linguistics algorithms. About This Book ? Discover the open source Python text analysis ecosystem, using spaCy, Gensim, scikit-learn, and Keras ? Hands-on text analysis with Python, featuring natural language processing and computational linguistics algorithms ? Learn deep learning techniques for text analysis Who This Book Is For This book is for you if you want to dive in, hands-first, into the interesting world of text analysis and NLP, and you're ready to work with the rich Python ecosystem of tools and datasets waiting for you! What You Will Learn ? Why text analysis is important in our modern age ? Understand NLP terminology and get to know the Python tools and datasets ? Learn how to pre-process and clean textual data ? Convert textual data into vector space representations ? Using spaCy to process text ? Train your own NLP models for computational linguistics ? Use statistical learning and Topic Modeling algorithms for text, using Gensim and scikit-learn ? Employ deep learning techniques for text analysis using Keras In Detail Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data. This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy. You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning. This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis. Style and approach The book teaches NLP from the angle of a practitioner as well as that of a student. This is a tad unusual, but given the enormous speed at which new algorithms and approaches travel from scientific beginnings to industrial implementation, first principles can be clarified with the help of entirely practical examples.

Explore the various packages in Julia that support image processing and build neural networks for video processing and object tracking. About This Book ? Build a full-fledged image processing application using JuliaImages ? Perform basic to advanced image and video stream processing with Julia's APIs ? Understand and optimize various features of OpenCV with easy examples Who This Book Is For Hands-On Computer Vision with Julia is for Julia developers who are interested in learning how to perform image processing and want to explore the field of computer vision. Basic knowledge of Julia will help you understand the concepts more effectively. What You Will Learn ? Analyze image metadata and identify critical data using JuliaImages ? Apply filters and improve image quality and color schemes ? Extract 2D features for image comparison using JuliaFeatures ? Cluster and classify images with KNN/SVM machine learning algorithms ? Recognize text in an image using the Tesseract library ? Use OpenCV to recognize specific objects or faces in images and videos ? Build neural network and classify images with MXNet In Detail Hands-On Computer Vision with Julia is a thorough guide for developers who want to get started with building computer vision applications using Julia. Julia is well suited to image processing because it’s easy to use and lets you write easy-to-compile and efficient machine code. This book begins by introducing you to Julia's image processing libraries such as Images.jl and ImageCore.jl. You’ll get to grips with analyzing and transforming images using JuliaImages; some of the techniques discussed include enhancing and adjusting images. As you make your way through the chapters, you’ll learn how to classify images, cluster them, and apply neural networks to solve computer vision problems. In the concluding chapters, you will explore OpenCV applications to perform real-time computer vision analysis, for example, face detection and object tracking. You will also understand Julia's interaction with Tesseract to perform optical character recognition and build an application that brings together all the techniques we introduced previously to consolidate the concepts learned. By end of the book, you will have understood how to utilize various Julia packages and a few open source libraries such as Tesseract and OpenCV to solve computer vision problems with ease. Style and approach Readers will be taken through various packages that support image processing in Julia, and will also tap into open-source libraries such as Open CV and Tesseract to find the optimum solution to problems encountered in computer vision.

Get up and running with the fundamentals of Amazon Alexa and build exciting IoT projects About This Book ? Gain hands-on experience of working with Amazon Echo and Alexa ? Build exciting IoT projects using Amazon Echo ? Learn about voice-enabled smart devices Who This Book Is For Alexa Skills Projects is for individuals who want to have a deep understanding of the underlying technology that drives Amazon Echo and Alexa, and how it can be integrated with the Internet of Things to develop hands-on projects. What You Will Learn ? Understand how Amazon Echo is already being used in various domains ? Discover how an Alexa Skill is architected ? Get a clear understanding of how some of the most popular Alexa Skills work ? Design Alexa Skills for specific purposes and interact with Amazon Echo to execute them ? Gain experience of programming for Amazon Echo ? Explore future applications of Amazon Echo and other voice-activated devices In Detail Amazon Echo is a smart speaker developed by Amazon, which connects to Amazon’s Alexa Voice Service and is entirely controlled by voice commands. Amazon Echo is currently being used for a variety of purposes such as home automation, asking generic queries, and even ordering a cab or pizza. Alexa Skills Projects starts with a basic introduction to Amazon Alexa and Echo. You will then deep dive into Alexa Programming concepts such as Intents, Slots, Lambdas and maintaining your skill’s state using DynamoDB. You will get a clear understanding of how some of the most popular Alexa Skills work, and gain experience of working with real-world Amazon Echo applications. In the concluding chapters, you will explore the future of voice-enabled applications and their coverage with respect to the Internet of Things. By the end of the book, you will have learned to design Alexa Skills for specific purposes and interact with Amazon Echo to execute these skills. Style and approach A practical guide filled with real world examples that will help you understand the process of creating Alexa Skills from scratch and it's real world applications.

Create interactive cross-platform games with the Godot Engine 3.0 About This Book ? Learn the art of developing cross-platform games ? Leverage Godot’s node and scene system to design robust, reusable game objects ? Integrate Blender easily and efficiently with Godot to create powerful 3D games Who This Book Is For Godot Engine Game Development Projects is for both new users and experienced developers, who want to learn to make games using a modern game engine. Some prior programming experience is recommended. What You Will Learn ? Get started with the Godot game engine and editor ? Organize a game project ? Import graphical and audio assets ? Use Godot’s node and scene system to design robust, reusable game objects ? Write code in GDScript to capture input and build complex behaviors ? Implement user interfaces to display information ? Create visual effects to spice up your game ? Learn techniques that you can apply to your own game projects In Detail Godot Engine Game Development Projects is an introduction to the Godot game engine and its new 3.0 version. Godot 3.0 brings a large number of new features and capabilities that make it a strong alternative to expensive commercial game engines. For beginners, Godot offers a friendly way to learn game development techniques, while for experienced developers it is a powerful, customizable tool that can bring your visions to life. This book consists of five projects that will help developers achieve a sound understanding of the engine when it comes to building games. Game development is complex and involves a wide spectrum of knowledge and skills. This book can help you build on your foundation level skills by showing you how to create a number of small-scale game projects. Along the way, you will learn how Godot works and discover important game development techniques that you can apply to your projects. Using a straightforward, step-by-step approach and practical examples, the book will take you from the absolute basics through to sophisticated game physics, animations, and other techniques. Upon completing the final project, you will have a strong foundation for future success with Godot 3.0. Style and approach The book is divided into five parts; each covering a different small-game project using a straightforward, step-by-step approach and practical examples. The book will take readers from the absolute basics through sophisticated game physics, animation, and other techniques.