Practical recipes to implement cost-effective and scalable cloud solutions for your organization About This Book ? Implement Google Cloud services in your organization ? Leverage Google Cloud components to secure your organization’s data ? A recipe-based guide that promises hands-on experience in deploying a highly scalable and available environment Who This Book Is For This book is for IT professionals, engineers, and developers looking at implementing Google Cloud in their organizations. Administrators and architects planning to make their organization more efficient with Google Cloud will also find this book useful. Basic understanding of Cloud services and the Google Cloud platform is necessary. What You Will Learn ? Host a Python application on Google Compute Engine ? Host an application using Google Cloud Functions ? Migrate a MySQL DB to Cloud Spanner ? Configure a network for a highly available application on GCP ? Learn simple image processing using Storage and Cloud Functions ? Automate security checks using Policy Scanner ? Understand tools for monitoring a production environment in GCP ? Learn to manage multiple projects using service accounts In Detail Google Cloud Platform is a cloud computing platform that offers products and services to host applications using state-of-the art infrastructure and technology. You can build and host applications and websites, store data, and analyze data on Google's scalable infrastructure. This book follows a recipe-based approach, giving you hands-on experience to make the most of Google Cloud services. This book starts with practical recipes that explain how to utilize Google Cloud's common services. Then, you'll see how to make full use of Google Cloud components such as networking, security, management, and developer tools. Next, we'll deep dive into implementing core Google Cloud services into your organization, with practical recipes on App Engine, Compute Engine microservices with Cloud Functions, virtual networks, and Cloud Storage. Later, we'll provide recipes on implementing authentication and security, Cloud APIs, command-line management, deployment management, and the Cloud SDK. Finally, we'll cover administration troubleshooting tasks with the Compute and Container Engines and we'll show how to monitor your organization's efficiency with best practices. By the end of this book, you'll have a complete understanding of how to implement Google Cloud services in your organization with ease. Style and approach This book will quickly get you started with using Google Cloud Services.

Unleash Google's Cloud Platform to build, train and optimize machine learning models About This Book ? Get well versed in GCP pre-existing services to build your own smart models ? A comprehensive guide covering aspects from data processing, analyzing to building and training ML models ? A practical approach to produce your trained ML models and port them to your mobile for easy access Who This Book Is For This book is for data scientists, machine learning developers and AI developers who want to learn Google Cloud Platform services to build machine learning applications. Since the interaction with the Google ML platform is mostly done via the command line, the reader is supposed to have some familiarity with the bash shell and Python scripting. Some understanding of machine learning and data science concepts will be handy What You Will Learn ? Use Google Cloud Platform to build data-based applications for dashboards, web, and mobile ? Create, train and optimize deep learning models for various data science problems on big data ? Learn how to leverage BigQuery to explore big datasets ? Use Google’s pre-trained TensorFlow models for NLP, image, video and much more ? Create models and architectures for Time series, Reinforcement Learning, and generative models ? Create, evaluate, and optimize TensorFlow and Keras models for a wide range of applications In Detail Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at scale but also host them in the cloud to make predictions. This book is focused on making the most of the Google Machine Learning Platform for large datasets and complex problems. You will learn from scratch how to create powerful machine learning based applications for a wide variety of problems by leveraging different data services from the Google Cloud Platform. Applications include NLP, Speech to text, Reinforcement learning, Time series, recommender systems, image classification, video content inference and many other. We will implement a wide variety of deep learning use cases and also make extensive use of data related services comprising the Google Cloud Platform ecosystem such as Firebase, Storage APIs, Datalab and so forth. This will enable you to integrate Machine Learning and data processing features into your web and mobile applications. By the end of this book, you will know the main difficulties that you may encounter and get appropriate strategies to overcome these difficulties and build efficient systems. Style and approach An easy-to-follow step by step guide which will help you get to the grips with real-world applications of Google Cloud Machine Learning.

Get familiar with the building blocks of IoT solutions using off–the-shelf IoT platforms. About This Book ? Work with various trending IoT platforms such as AWS IoT, Azure IoT, Google IoT, IBM Watson IoT, and Kaa IoT ? Gain hands-on knowledge working with Cloud-based IoT platforms, IoT Analytics, and so on. ? A practical guide that will help you build IoT strategies for your organization Who This Book Is For This book is targeted at IoT architects and engineers, or any stakeholders working with IoT solutions in an organization. This book will also help decision makers and professionals from small- and medium-sized enterprises build an IoT strategy for their venture. What You Will Learn ? Connect a Temperature and Humidity sensor and see how these two can be managed from various platforms ? Explore the core components of AWS IoT such as AWS Kinesis and AWS IoTRules Engine ? Build a simple analysis dashboard using Azure IoT and Power BI ? Understand the fundamentals of Google IoT and use Google core APIs to build your own dashboard ? Get started and work with the IBM Watson IoT platform ? Integrate Cassandra and Zeppelin with Kaa IoT dashboard ? Review some Machine Learning and AI and get to know more about their implementation in the IoT domain. In Detail There is a lot of work that is being done in the IoT domain and according to Forbes the global IoT market will grow from $157B in 2016 to $457B by 2020. This is an amazing market both in terms technology advancement as well as money. In this book, we will be covering five popular IoT platforms, namely, AWS IoT, Microsoft Azure IoT, Google IoT Core, IBM Watson IoT, and Kaa IoT middleware. You are going to build solutions that will use a Raspberry Pi 3, a DHT11 Temperature and humidity sensor, and a dashboard to visualize the sensor data in real-time. Furthermore, you will also explore various components of each of the platforms that are needed to achieve the desired solution. Besides building solutions, you will look at how Machine Learning and IoT go hand in hand and later design a simple predictive web service based on this concept. By the end of this book, you will be in a position to implement an IoT strategy best-fit for your organization Style and approach An informative guide that will help you design and implement an IoT Strategy best-fit for your organization

A recipe-based guide to programming your Raspberry Pi 3 using Python About This Book : ? Leverage the power of Raspberry Pi 3 using Python programming ? Create 3D games, build neural network modules, and interface with your own circuits ? Packed with clear, step-by-step recipes to walk you through the capabilities of Raspberry Pi Who This Book Is For : This book is for anyone who wants to master the skills of Python programming using Raspberry Pi 3. Prior knowledge of Python will be an added advantage. What You Will Learn : ? Learn to set up and run Raspberry Pi 3 ? Build text classifiers and perform automation using Python ? Predict sentiments in words and create games and graphics ? Detect edges and contours in images ? Build human face detection and recognition system ? Use Python to drive hardware ? Sense and display real-world data ? Build a neural network module for optical character recognition ? Build movie recommendations system In Detail : Raspberry Pi 3 Cookbook for Python Programmers – Third Edition begins by guiding you through setting up Raspberry Pi 3, performing tasks using Python 3.6, and introducing the first steps to interface with electronics. As you work through each chapter, you will build your skills and apply them as you progress. You will learn how to build text classifiers, predict sentiments in words, develop applications using the popular Tkinter library, and create games by controlling graphics on your screen. You will harness the power of a built in graphics processor using Pi3D to generate your own high-quality 3D graphics and environments. You will understand how to connect Raspberry Pi’s hardware pins directly to control electronics, from switching on LEDs and responding to push buttons to driving motors and servos. Get to grips with monitoring sensors to gather real-life data, using it to control other devices, and viewing the results over the internet. You will apply what you have learned by creating your own Pi-Rover or Pi-Hexipod robots. You will also learn about sentiment analysis, face recognition techniques, and building neural network modules for optical character recognition. Finally, you will learn to build movie recommendations system on Raspberry Pi 3. Style and approach : Written in a cookbook style, this book contains a series of recipes on various topics. It is an easy-to-follow step-by-step guide with examples of feature integration suitable for any search application.

A practical guide for building effective enterprise solutions with Java EE 8 About This Book ? Recipes to get you up-and-running with Java EE 8 application development ? Learn how to apply the major Java EE 8 APIs and specifications ? Implement microservices and Reactive programming with Java EE 8 Who This Book Is For This book is for developers who want to become proficient with Java EE 8 for their enterprise application development. Basic knowledge of Java is assumed What You Will Learn ? Actionable information on the new features of Java EE 8 ? Using the most important APIs with real and working code ? Building server side applications, web services, and web applications ? Deploying and managing your application using the most important Java EE servers ? Building and deploying microservices using Java EE 8 ? Building Reactive application by joining Java EE APIs and core Java features ? Moving your application to the cloud using containers ? Practical ways to improve your projects and career through community involvement In Detail Java EE is a collection of technologies and APIs to support Enterprise Application development. The choice of what to use and when can be dauntingly complex for any developer. This book will help you master this. Packed with easy to follow recipes, this is your guide to becoming productive with Java EE 8. You will begin by seeing the latest features of Java EE 8, including major Java EE 8 APIs and specifications such as JSF 2.3, and CDI 2.0, and what they mean for you. You will use the new features of Java EE 8 to implement web-based services for your client applications. You will then learn to process the Model and Streaming APIs using JSON-P and JSON-B and will learn to use the Java Lambdas support offered in JSON-P. There are more recipes to fine-tune your RESTful development, and you will learn about the Reactive enhancements offered by the JAX-RS 2.1 specification. Later on, you will learn about the role of multithreading in your enterprise applications and how to integrate them for transaction handling. This is followed by implementing microservices with Java EE and the advancements made by Java EE for cloud computing. The final set of recipes shows you how take advantage of the latest security features and authenticate your enterprise application. At the end of the book, the Appendix shows you how knowledge sharing can change your career and your life. Style and approach Task based learning guide to help ease application development with Java EE.

Mastering advanced features of Java and implement them to build amazing projects About This Book ? Take advantage of Java's new modularity features to write real-world applications that solve a variety of problems ? Explore the major concepts introduced with Java 9, including modular programming, HTTP 2.0, API changes, and more ? Get to grips with tools, techniques and best practices to enhance application development Who This Book Is For This learning path is for Java developers who are looking to move a level up and learn how to build robust applications in the latest version of Java. What You Will Learn ? Package Java applications as modules using the Java Platform Module System ? Implement process management in Java using the all-new process handling API ? Integrate your applications with third-party services in the cloud ? Interact with mail servers, using JavaMail to build an application that filters spam messages ? Use JavaFX to build rich GUI-based applications, which are an essential element of application development ? Leverage the possibilities provided by the newly introduced Java shell ? Test your application's effectiveness with the JVM harness ? See how Java 9 provides support for the HTTP 2.0 standard In Detail Java 9 and its new features add to the richness of the language; Java is one of the languages most used by developers to build robust software applications. Java 9 comes with a special emphasis on modularity with its integration with Jigsaw. This course is your one-stop guide to mastering the language. You'll be provided with an overview and explanation of the new features introduced in Java 9 and the importance of the new APIs and enhancements. Some new features of Java 9 are ground-breaking; if you are an experienced programmer, you will be able to make your enterprise applications leaner by learning these new features. You'll be provided with practical guidance in applying your newly acquired knowledge of Java 9 and further information on future developments of the Java platform. This course will improve your productivity, making your applications faster. Next, you'll go on to implement everything you've learned by building 10 cool projects. You will learn to build an email filter that separates spam messages from all your inboxes, a social media aggregator app that will help you efficiently track various feeds, and a microservice for a client/server note application, to name just a few. By the end of this course, you will be well acquainted with Java 9 features and able to build your own applications and projects. This Learning Path contains the best content from the following two recently published Packt products: ? Mastering Java 9 ? Java 9 Programming Blueprints Style and approach This practical guide is filled with real-world examples. Its projects will help you get acquainted with concepts in depth.

Add a touch of data analytics to your healthcare systems and get insightful outcomes Key Features *Perform healthcare analytics with Python and SQL *Build predictive models on real healthcare data with pandas and scikit-learn *Use analytics to improve healthcare performance Book Description In recent years, machine learning technologies and analytics have been widely utilized across the healthcare sector. Healthcare Analytics Made Simple bridges the gap between practising doctors and data scientists. It equips the data scientists’ work with healthcare data and allows them to gain better insight from this data in order to improve healthcare outcomes. This book is a complete overview of machine learning for healthcare analytics, briefly describing the current healthcare landscape, machine learning algorithms, and Python and SQL programming languages. The step-by-step instructions teach you how to obtain real healthcare data and perform descriptive, predictive, and prescriptive analytics using popular Python packages such as pandas and scikit-learn. The latest research results in disease detection and healthcare image analysis are reviewed. By the end of this book, you will understand how to use Python for healthcare data analysis, how to import, collect, clean, and refine data from electronic health record (EHR) surveys, and how to make predictive models with this data through real-world algorithms and code examples. What you will learn *Gain valuable insight into healthcare incentives, finances, and legislation *Discover the connection between machine learning and healthcare processes *Use SQL and Python to analyze data *Measure healthcare quality and provider performance *Identify features and attributes to build successful healthcare models *Build predictive models using real-world healthcare data *Become an expert in predictive modeling with structured clinical data *See what lies ahead for healthcare analytics Who this book is for Healthcare Analytics Made Simple is for you if you are a developer who has a working knowledge of Python or a related programming language, although you are new to healthcare or predictive modeling with healthcare data. Clinicians interested in analytics and healthcare computing will also benefit from this book. This book can also serve as a textbook for students enrolled in an introductory course on machine learning for healthcare.

Get up and running with AWS automation using CloudFormation Key Features *Explore the fundamentals of AWS CloudFormation *Get acquainted with concepts such as CloudFormation templates and mappings *Learn to implement Infrastructure as a Code (IaC) on AWS Book Description As the Amazon Web Services (AWS) infrastructure is gradually moving towards cloud, managing cloud-related tasks efficiently continues to be a challenge for system administrators. CloudFormation is a language developed for managing infrastructure-related services efficiently on AWS and its features help secure the AWS resource deployment process. Learn CloudFormation serves as a fundamental guide to kick-start your journey on CloudFormation. We will introduce you to the basic concepts on IaC and the AWS services required for implementing automation and infrastructure management. Then, we deep dive into concepts such as CloudFormation mapping, conditions, limit, and output and EC2. In the concluding chapters, you will manage the entire AWS infrastructure using CloudFormation templates. By the end of this book, you will get up and running with IaC with CloudFormation. What you will learn *Understand AWS CloudFormation *Develop AWS CloudFormation templates *Deploy AWS CloudFormation for AWS resources *Build your first AWS CloudFormation project *Explore AWS Security features *Deploy testing and production stages using CloudFormation Who this book is for Learn CloudFormation is for cloud engineers, system administrators, cloud architects, or any stakeholders working in the field of cloud development or cloud administration. Basic knowledge of AWS is necessary.

Discover how you can migrate a traditional on-premise SQL server database to a cloud-based solution with Microsoft Azure. Built with database administrators in mind, this book emulates different scenarios you might come across while working with large, complex SQL database migrations and provides solutions for effectively managing the migrated databases. Key Features *Implement backup, restore, and recovery of Azure SQL databases *Create shards and elastic pools to scale Azure SQL databases *Automate common management tasks with PowerShell *Implement over 40 practical activities and exercises across 24 topics to reinforce your learning Book Description As the cloud version of SQL Server, Azure SQL Database differs in key ways when it comes to management, maintenance, and administration. It’s important to know how to administer SQL Database to fully benefit from all of the features and functionality that it provides. This book addresses important aspects of an Azure SQL Database instance such as migration, backup restorations, pricing policies, security, scalability, monitoring, performance optimization, high availability, and disaster recovery. It is a complete guide for database administrators, and ideal for those who are planning to migrate from on premise SQL Server database to an Azure SQL Server database. What you will learn *Learn how to provision a new database or migrate an existing on-premise solution *Understand how to backup, restore, secure, and scale your own Azure SQL Database *Optimize the performance by monitoring and tuning your cloud-based SQL instance *Implement high availability and disaster recovery procedures with SQL Database *Develop a roadmap for your own scalable cloud solution with Azure SQL Database Who this book is for This book is ideal for database administrators, database developers, or application developers who are interested in developing or migrating existing applications with Azure SQL Database. Prior experience of working with an on-premise SQL Server deployment and brief knowledge of PowerShell and C# are recommended prerequisites.

Bridge the gap between developer and data scientist by creating a modern open-source, Python-based toolset that works with Jupyter Notebook, and PixieDust. Key Features *Think deeply as a developer about your strategy and toolset in data science *Discover the best tools that will suit you as a developer in your data analysis *Accelerate the road to data insight as a programmer using Jupyter Notebook *Deep dive into multiple industry data science use cases Book Description Thoughtful Data Science brings new strategies and a carefully crafted programmer's toolset to work with modern, cutting-edge data analysis. This new approach is designed specifically to give developers more efficiency and power to create cutting-edge data analysis and artificial intelligence insights. Industry expert David Taieb bridges the gap between developers and data scientists by creating a modern open-source, Python-based toolset that works with Jupyter Notebook, and PixieDust. You'll find the right balance of strategic thinking and practical projects throughout this book, with extensive code files and Jupyter projects that you can integrate with your own data analysis. David Taieb introduces four projects designed to connect developers to important industry use cases in data science. The first is an image recognition application with TensorFlow, to meet the growing importance of AI in data analysis. The second analyses social media trends to explore big data issues and natural language processing. The third is a financial portfolio analysis application using time series analysis, pivotal in many data science applications today. The fourth involves applying graph algorithms to solve data problems. Taieb wraps up with a deep look into the future of data science for developers and his views on AI for data science. What you will learn *Bridge the gap between developer and data scientist with a Python-based toolset *Get the most out of Jupyter Notebooks with new productivity-enhancing tools *Explore and visualize data using Jupyter Notebooks and PixieDust *Work with and assess the impact of artificial intelligence in data science *Work with TensorFlow, graphs, natural language processing, and time series *Deep dive into multiple industry data science use cases *Look into the future of data analysis and where to develop your skills Who this book is for This book is for established developers who want to bridge the gap between programmers and data scientists. With the introduction of PixieDust from its creator, the book will also be a great desk companion for the already accomplished Data Scientist. Some fluency in data interpretation and visualization is also assumed since this book addresses data professionals such as business and general data analysts. It will be helpful to have some knowledge of Python, using Python libraries, and some proficiency in web development.

Getting started with data science doesn't have to be an uphill battle. This step-by-step guide is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction. About This Book ? Get up and running with the Jupyter ecosystem and some example datasets ? Learn about key machine learning concepts like SVM, KNN classifiers and Random Forests ? Discover how you can use web scraping to gather and parse your own bespoke datasets Who This Book Is For This book is ideal for professionals with a variety of job descriptions across large range of industries, given the rising popularity and accessibility of data science. You'll need some prior experience with Python, with any prior work with libraries like Pandas, Matplotlib and Pandas providing you a useful head start. What You Will Learn ? Identify potential areas of investigation and perform exploratory data analysis ? Plan a machine learning classification strategy and train classification models ? Use validation curves and dimensionality reduction to tune and enhance your models ? Scrape tabular data from web pages and transform it into Pandas DataFrames ? Create interactive, web-friendly visualizations to clearly communicate your findings In Detail Get to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course. You'll learn about some of the most commonly used libraries that are part of the Anaconda distribution, and then explore machine learning models with real datasets to give you the skills and exposure you need for the real world. We'll finish up by showing you how easy it can be to scrape and gather your own data from the open web, so that you can apply your new skills in an actionable context. Style and approach This book covers every aspect of the standard data-workflow process within a day, along with theory, practical hands-on coding, and relatable illustrations.

A hands-on guide to creating, monitoring, and tuning a high performance Spring web application About This Book ? Understand common performance pitfalls and improve your application's performance ? Build and deploy strategies for complex applications using the microservice architecture ? Understand internals of JVM - the core of all Java Runtime Environments Who This Book Is For If you’re a Spring developer who’d like to build high performance applications and have more control over your application's performance in production and development, this book is for you. Some familiarity with Java, Maven, and Eclipse is necessary. What You Will Learn ? Master programming best practices and performance improvement with bean wiring ? Analyze the performance of various AOP implementations ? Explore database interactions with Spring to optimize design and configuration ? Solve Hibernate performance issues and traps ? Leverage multithreading and concurrent programming to improve application performance ? Gain a solid foundation in JVM performance tuning using various tools ? Learn the key concepts of the microservice architecture and how to monitor them ? Perform Spring Boot performance tuning, monitoring, and health checks In Detail While writing an application, performance is paramount. Performance tuning for real-world applications often involves activities geared toward detecting bottlenecks. The recent release of Spring 5.0 brings major advancements in the rich API provided by the Spring framework, which means developers need to master its tools and techniques to achieve high performance applications. Hands-On High Performance with Spring 5 begins with the Spring framework's core features, exploring the integration of different Spring projects. It proceeds to evaluate various Spring specifications to identify those adversely affecting performance. You will learn about bean wiring configurations, aspect-oriented programming, database interaction, and Hibernate to focus on the metrics that help identify performance bottlenecks. You will also look at application monitoring, performance optimization, JVM internals, and garbage collection optimization. Lastly, the book will show you how to leverage the microservice architecture to build a high performance and resilient application. By the end of the book, you will have gained an insight into various techniques and solutions to build and troubleshoot high performance Spring-based applications. Style and approach This book takes a step-by-step approach with focused examples to teach you how to increase application performance.

Find out how to write Kotlin code without overhead and how to use different profiling tools and bytecode viewer to inspect expressions of Kotlin language. About This Book ? Apply modern Kotlin features to speed up processing and implement highly efficient and reliable codes. ? Learn memory optimization, concurrency, multi-threading, scaling, and caching techniques to achieve high performance. ? Learn how to prevent unnecessary overhead and use profiling tools to detect performance issues. Who This Book Is For This book is for Kotlin developers who would like to build reliable and high-performance applications. Prior Kotlin programming knowledge is assumed. What You Will Learn ? Understand the importance of high performance ? Learn performance metrics ? Learn popular design patterns currently being used in Kotlin ? Understand how to apply modern Kotlin features to data processing ? Learn how to use profling tools ? Discover how to read bytecode ? Learn to perform memory optimizations ? Uncover approaches to the multithreading environment In Detail The ease with which we write applications has been increasing, but with it comes the need to address their performance. A balancing act between easily implementing complex applications and keeping their performance optimal is a present-day requirement In this book, we explore how to achieve this crucial balance, while developing and deploying applications with Kotlin. The book starts by analyzing various Kotlin specifcations to identify those that have a potentially adverse effect on performance. Then, we move on to monitor techniques that enable us to identify performance bottlenecks and optimize performance metrics. Next, we look at techniques that help to us achieve high performance: memory optimization, concurrency, multi threading, scaling, and caching. We also look at fault tolerance solutions and the importance of logging. We'll also cover best practices of Kotlin programming that will help you to improve the quality of your code base. By the end of the book, you will have gained some insight into various techniques and solutions that will help to create high-performance applications in the Kotlin environment Style and approach This book guides you through how to use profiling tools to detect performance issues and build high-performance applications in the Kotlin environment.

This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems. About This Book ? Explore deep reinforcement learning (RL), from the first principles to the latest algorithms ? Evaluate high-profile RL methods, including value iteration, deep Q-networks, policy gradients, TRPO, PPO, DDPG, D4PG, evolution strategies and genetic algorithms ? Keep up with the very latest industry developments, including AI-driven chatbots Who This Book Is For Some fluency in Python is assumed. Basic deep learning (DL) approaches should be familiar to readers and some practical experience in DL will be helpful. This book is an introduction to deep reinforcement learning (RL) and requires no background in RL. What You Will Learn ? Understand the DL context of RL and implement complex DL models ? Learn the foundation of RL: Markov decision processes ? Evaluate RL methods including Cross-entropy, DQN, Actor-Critic, TRPO, PPO, DDPG, D4PG and others ? Discover how to deal with discrete and continuous action spaces in various environments ? Defeat Atari arcade games using the value iteration method ? Create your own OpenAI Gym environment to train a stock trading agent ? Teach your agent to play Connect4 using AlphaGo Zero ? Explore the very latest deep RL research on topics including AI-driven chatbots In Detail Recent developments in reinforcement learning (RL), combined with deep learning (DL), have seen unprecedented progress made towards training agents to solve complex problems in a human-like way. Google's use of algorithms to play and defeat the well-known Atari arcade games has propelled the field to prominence, and researchers are generating new ideas at a rapid pace. Deep Reinforcement Learning Hands-On is a comprehensive guide to the very latest DL tools and their limitations. You will evaluate methods including Cross-entropy and policy gradients, before applying them to real-world environments. Take on both the Atari set of virtual games and family favorites such as Connect4. The book provides an introduction to the basics of RL, giving you the know-how to code intelligent learning agents to take on a formidable array of practical tasks. Discover how to implement Q-learning on 'grid world' environments, teach your agent to buy and trade stocks, and find out how natural language models are driving the boom in chatbots. Style and approach Deep Reinforcement Learning Hands-On explains the art of building self-learning agents using algorithms and practical examples. Experiment with famous examples, such as Google's defeat of well-known Atari arcade games.

Develop efficient and modern full-stack applications using Spring Boot and React 16 About This Book ? Develop resourceful backends using Spring Boot and faultless frontends using React. ? Explore the techniques involved in creating a full-stack app by going through a methodical approach. ? Learn to add CRUD functionalities and use Material UI in the user interface to make it more user-friendly. Who This Book Is For Java developers who are familiar with Spring, but have not yet built full-stack applications What You Will Learn ? Create a RESTful web service with Spring Boot ? Understand how to use React for frontend programming ? Gain knowledge of how to create unit tests using JUnit ? Discover the techniques that go into securing the backend using Spring Security ? Learn how to use Material UI in the user interface to make it more user-friendly ? Create a React app by using the Create React App starter kit made by Facebook In Detail Apart from knowing how to write frontend and backend code, a full-stack engineer has to tackle all the problems that are encountered in the application development life cycle, starting from a simple idea to UI design, the technical design, and all the way to implementing, testing, production, deployment, and monitoring. This book covers the full set of technologies that you need to know to become a full-stack web developer with Spring Boot for the backend and React for the frontend. This comprehensive guide demonstrates how to build a modern full-stack application in practice. This book will teach you how to build RESTful API endpoints and work with the data access Layer of Spring, using Hibernate as the ORM. As we move ahead, you will be introduced to the other components of Spring, such as Spring Security, which will teach you how to secure the backend. Then, we will move on to the frontend, where you will be introduced to React, a modern JavaScript library for building fast and reliable user interfaces, and its app development environment and components. You will also create a Docker container for your application. Finally, the book will lay out the best practices that underpin professional full-stack web development. Style and approach A step-by-step guide to building full-stack applications along with best practices to make your Full-stack development journey easier

Get acquainted with GCP and manage robust, highly available, and dynamic solutions to drive business objective About This Book ? Identify the strengths, weaknesses and ideal use-cases for individual services offered on the Google Cloud Platform ? Make intelligent choices about which cloud technology works best for your use-case ? Leverage Google Cloud Platform to analyze and optimize technical and business processes Who This Book Is For If you are a Cloud architect who is responsible to design and manage robust cloud solutions with Google Cloud Platform, then this book is for you. System engineers and Enterprise architects will also find this book useful. A basic understanding of distributed applications would be helpful, although not strictly necessary. Some working experience on other public cloud platforms would help too. What You Will Learn ? Set up GCP account and utilize GCP services using the cloud shell, web console, and client APIs ? Harness the power of App Engine, Compute Engine, Containers on the Kubernetes Engine, and Cloud Functions ? Pick the right managed service for your data needs, choosing intelligently between Datastore, BigTable, and BigQuery ? Migrate existing Hadoop, Spark, and Pig workloads with minimal disruption to your existing data infrastructure, by using Dataproc intelligently ? Derive insights about the health, performance, and availability of cloud-powered applications with the help of monitoring, logging, and diagnostic tools in Stackdriver In Detail Using a public cloud platform was considered risky a decade ago, and unconventional even just a few years ago. Today, however, use of the public cloud is completely mainstream - the norm, rather than the exception. Several leading technology firms, including Google, have built sophisticated cloud platforms, and are locked in a fierce competition for market share. The main goal of this book is to enable you to get the best out of the GCP, and to use it with confidence and competence. You will learn why cloud architectures take the forms that they do, and this will help you become a skilled high-level cloud architect. You will also learn how individual cloud services are configured and used, so that you are never intimidated at having to build it yourself. You will also learn the right way and the right situation in which to use the important GCP services. By the end of this book, you will be able to make the most out of Google Cloud Platform design. Style and approach A clear, concise, and straightforward book which will enable to develop and manage optimum solutions for your infrastructure

Create various design patterns to master the art of solving problems using Java About This Book ? This book demonstrates the shift from OOP to functional programming and covers reactive and functional patterns in a clear and step-by-step manner ? All the design patterns come with a practical use case as part of the explanation, which will improve your productivity ? Tackle all kinds of performance-related issues and streamline your development Who This Book Is For This book is for those who are familiar with Java development and want to be in the driver’s seat when it comes to modern development techniques. Basic OOP Java programming experience and elementary familiarity with Java is expected. What You Will Learn ? Understand the OOP and FP paradigms ? Explore the traditional Java design patterns ? Get to know the new functional features of Java ? See how design patterns are changed and affected by the new features ? Discover what reactive programming is and why is it the natural augmentation of FP ? Work with reactive design patterns and find the best ways to solve common problems using them ? See the latest trends in architecture and the shift from MVC to serverless applications ? Use best practices when working with the new features In Detail Having a knowledge of design patterns enables you, as a developer, to improve your code base, promote code reuse, and make the architecture more robust. As languages evolve, new features take time to fully understand before they are adopted en masse. The mission of this book is to ease the adoption of the latest trends and provide good practices for programmers. We focus on showing you the practical aspects of smarter coding in Java. We'll start off by going over object-oriented (OOP) and functional programming (FP) paradigms, moving on to describe the most frequently used design patterns in their classical format and explain how Java’s functional programming features are changing them. You will learn to enhance implementations by mixing OOP and FP, and finally get to know about the reactive programming model, where FP and OOP are used in conjunction with a view to writing better code. Gradually, the book will show you the latest trends in architecture, moving from MVC to microservices and serverless architecture. We will finish off by highlighting the new Java features and best practices. By the end of the book, you will be able to efficiently address common problems faced while developing applications and be comfortable working on scalable and maintainable projects of any size. Style and approach This book explains design patterns in a step-by-step manner with clear and concise code explanations.

Become a master at penetration testing using machine learning with Python About This Book ? Identify ambiguities and breach intelligent security systems ? Perform unique cyber attacks to breach robust systems ? Learn to leverage machine learning algorithms Who This Book Is For This book is for pen testers and security professionals who are interested in learning techniques to break an intelligent security system. Basic knowledge of Python is needed, but no prior knowledge of machine learning is necessary. What You Will Learn ? Take an in-depth look at machine learning ? Get to know natural language processing (NLP) ? Understand malware feature engineering ? Build generative adversarial networks using Python libraries ? Work on threat hunting with machine learning and the ELK stack ? Explore the best practices for machine learning In Detail Cyber security is crucial for both businesses and individuals. As systems are getting smarter, we now see machine learning interrupting computer security. With the adoption of machine learning in upcoming security products, it’s important for pentesters and security researchers to understand how these systems work, and to breach them for testing purposes. This book begins with the basics of machine learning and the algorithms used to build robust systems. Once you’ve gained a fair understanding of how security products leverage machine learning, you'll dive into the core concepts of breaching such systems. Through practical use cases, you’ll see how to find loopholes and surpass a self-learning security system. As you make your way through the chapters, you’ll focus on topics such as network intrusion detection and AV and IDS evasion. We’ll also cover the best practices when identifying ambiguities, and extensive techniques to breach an intelligent system. By the end of this book, you will be well-versed with identifying loopholes in a self-learning security system and will be able to efficiently breach a machine learning system. Style and approach This book takes a step-by-step approach to identify the loop holes in a self-learning security system. You will be able to efficiently breach a machine learning system with the help of best practices towards the end of the book.

Leverage the simplicity of Python and available libraries to build web security testing tools for your application About This Book ? Understand the web application penetration testing methodology and toolkit using Python ? Write a web crawler/spider with the Scrapy library ? Detect and exploit SQL injection vulnerabilities by creating a script all by yourself Who This Book Is For Learning Python Web Penetration Testing is for web developers who want to step into the world of web application security testing. Basic knowledge of Python is necessary. What You Will Learn ? Interact with a web application using the Python and Requests libraries ? Create a basic web application crawler and make it recursive ? Develop a brute force tool to discover and enumerate resources such as files and directories ? Explore different authentication methods commonly used in web applications ? Enumerate table names from a database using SQL injection ? Understand the web application penetration testing methodology and toolkit In Detail Web penetration testing is the use of tools and code to attack a website or web app in order to assess its vulnerability to external threats. While there are an increasing number of sophisticated, ready-made tools to scan systems for vulnerabilities, the use of Python allows you to write system-specific scripts, or alter and extend existing testing tools to find, exploit, and record as many security weaknesses as possible. Learning Python Web Penetration Testing will walk you through the web application penetration testing methodology, showing you how to write your own tools with Python for each activity throughout the process. The book begins by emphasizing the importance of knowing how to write your own tools with Python for web application penetration testing. You will then learn to interact with a web application using Python, understand the anatomy of an HTTP request, URL, headers and message body, and later create a script to perform a request, and interpret the response and its headers. As you make your way through the book, you will write a web crawler using Python and the Scrappy library. The book will also help you to develop a tool to perform brute force attacks in different parts of the web application. You will then discover more on detecting and exploiting SQL injection vulnerabilities. By the end of this book, you will have successfully created an HTTP proxy based on the mitmproxy tool. Style and approach A easy-to-follow guide that will help you build different web application security testing tools. With each chapter building on the knowledge of the previous section, this book will help you to smartly assess the security needs of your apps.

Run Ansible playbooks to launch complex multi-tier applications hosted in public clouds About This Book ? Build your learning curve using Ansible ? Automate cloud, network, and security infrastructures with ease ? Gain hands-on exposure on Ansible Who This Book Is For Learn Ansible is perfect for system administrators and developers who want to take their current workflows and transform them into repeatable playbooks using Ansible. No prior knowledge of Ansible is required. What You Will Learn ? Write your own playbooks to configure servers running CentOS, Ubuntu, and Windows ? Identify repeatable tasks and write playbooks to automate them ? Define a highly available public cloud infrastructure in code, making it easy to distribute your infrastructure configuration ? Deploy and configure Ansible Tower and Ansible AWX ? Learn to use community contributed roles ? Use Ansible in your day-to-day role and projects In Detail Ansible has grown from a small, open source orchestration tool to a full-blown orchestration and configuration management tool owned by Red Hat. Its powerful core modules cover a wide range of infrastructures, including on-premises systems and public clouds, operating systems, devices, and services—meaning it can be used to manage pretty much your entire end-to-end environment. Trends and surveys say that Ansible is the first choice of tool among system administrators as it is so easy to use. This end-to-end, practical guide will take you on a learning curve from beginner to pro. You'll start by installing and configuring the Ansible to perform various automation tasks. Then, we'll dive deep into the various facets of infrastructure, such as cloud, compute and network infrastructure along with security. By the end of this book, you'll have an end-to-end understanding of Ansible and how you can apply it to your own environments. Style and approach A hands-on approach to give you practical experience of writing playbooks and roles and executing them. At the end of each chapter, you’ll find test questions to test your knowledge on Ansible.

This book gives you the skills you need to use Python for penetration testing, with the help of detailed code examples. This book has been updated for Python 3.6.3 and Kali Linux 2018.1. About This Book ? Detect and avoid various attack types that put the privacy of a system at risk ? Leverage Python to build efficient code and eventually build a robust environment ? Learn about securing wireless applications and information gathering on a web server Who This Book Is For If you are a Python programmer, a security researcher, or an ethical hacker and are interested in penetration testing with the help of Python, then this book is for you. Even if you are new to the field of ethical hacking, this book can help you find the vulnerabilities in your system so that you are ready to tackle any kind of attack or intrusion. What You Will Learn ? The basics of network pentesting including network scanning and sniffing ? Wireless, wired attacks, and building traps for attack and torrent detection ? Web server footprinting and web application attacks, including the XSS and SQL injection attack ? Wireless frames and how to obtain information such as SSID, BSSID, and the channel number from a wireless frame using a Python script ? The importance of web server signatures, email gathering, and why knowing the server signature is the first step in hacking In Detail This book gives you the skills you need to use Python for penetration testing (pentesting), with the help of detailed code examples. We start by exploring the basics of networking with Python and then proceed to network hacking. Then, you will delve into exploring Python libraries to perform various types of pentesting and ethical hacking techniques. Next, we delve into hacking the application layer, where we start by gathering information from a website. We then move on to concepts related to website hacking—such as parameter tampering, DDoS, XSS, and SQL injection. By reading this book, you will learn different techniques and methodologies that will familiarize you with Python pentesting techniques, how to protect yourself, and how to create automated programs to find the admin console, SQL injection, and XSS attacks. Style and approach The book starts at a basic level and moves to a higher level of network and web security. The execution and performance of code are both taken into account.