Discover the latest features of Spring framework by building robust, fast, and reactive web applications Key Features * Take advantage of all the features of Spring 5.0 with third party tools to build a robust back end * Secure Spring based web application using Spring Security framework with LDAP and OAuth protocol * Develop robust and scalable microservice based applications on Spring Cloud, using Spring Boot Book Description Spring makes it easy to create RESTful applications, merge with social services, communicate with modern databases, secure your system, and make your code modular and easy to test. With the arrival of Spring Boot, developers can really focus on the code and deliver great value, with minimal contour. This book will show you how to build various projects in Spring 5.0, using its features and third party tools. We'll start by creating a web application using Spring MVC, Spring Data, the World Bank API for some statistics on different countries, and MySQL database. Moving ahead, you'll build a RESTful web services application using Spring WebFlux framework. You'll be then taken through creating a Spring Boot-based simple blog management system, which uses Elasticsearch as the data store. Then, you'll use Spring Security with the LDAP libraries for authenticating users and create a central authentication and authorization server using OAuth 2 protocol. Further, you'll understand how to create Spring Boot-based monolithic application using JHipster. Toward the end, we'll create an online book store with microservice architecture using Spring Cloud and Net?ix OSS components, and a task management system using Spring and Kotlin. By the end of the book, you'll be able to create coherent and ?exible real-time web applications using Spring Framework. What you will learn * Build Spring based application using Bootstrap template and JQuery * Understand the Spring WebFlux framework and how it uses Reactor library * Interact with Elasticsearch for indexing, querying, and aggregating data * Create a simple monolithic application using JHipster * Use Spring Security and Spring Security LDAP and OAuth libraries for Authentication * Develop a microservice-based application with Spring Cloud and Netflix * Work on Spring Framework with Kotlin Who this book is for This book is for competent Spring developers who wish to understand how to develop complex yet flexible applications with Spring. You must have a good knowledge of Java programming and be familiar with the basics of Spring.

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

Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras Key Features *Implement machine learning algorithms to build, train, and validate algorithmic models *Create your own algorithmic design process to apply probabilistic machine learning approaches to trading decisions *Develop neural networks for algorithmic trading to perform time series forecasting and smart analytics Book Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies. This book shows how to access market, fundamental, and alternative data via API or web scraping and offers a framework to evaluate alternative data. You’ll practice the ML work?ow from model design, loss metric definition, and parameter tuning to performance evaluation in a time series context. You will understand ML algorithms such as Bayesian and ensemble methods and manifold learning, and will know how to train and tune these models using pandas, statsmodels, sklearn, PyMC3, xgboost, lightgbm, and catboost. This book also teaches you how to extract features from text data using spaCy, classify news and assign sentiment scores, and to use gensim to model topics and learn word embeddings from financial reports. You will also build and evaluate neural networks, including RNNs and CNNs, using Keras and PyTorch to exploit unstructured data for sophisticated strategies. Finally, you will apply transfer learning to satellite images to predict economic activity and use reinforcement learning to build agents that learn to trade in the OpenAI Gym. What you will learn *Implement machine learning techniques to solve investment and trading problems *Leverage market, fundamental, and alternative data to research alpha factors *Design and fine-tune supervised, unsupervised, and reinforcement learning models *Optimize portfolio risk and performance using pandas, NumPy, and scikit-learn *Integrate machine learning models into a live trading strategy on Quantopian *Evaluate strategies using reliable backtesting methodologies for time series *Design and evaluate deep neural networks using Keras, PyTorch, and TensorFlow *Work with reinforcement learning for trading strategies in the OpenAI Gym Who this book is for Hands-On Machine Learning for Algorithmic Trading is for data analysts, data scientists, and Python developers, as well as investment analysts and portfolio managers working within the finance and investment industry. If you want to perform efficient algorithmic trading by developing smart investigating strategies using machine learning algorithms, this is the book for you. Some understanding of Python and machine learning techniques is mandatory.

Speed up the design and implementation of deep learning solutions using Apache Spark Key Features * Explore the world of distributed deep learning with Apache Spark * Train neural networks with deep learning libraries such as BigDL and TensorFlow * Develop Spark deep learning applications to intelligently handle large and complex datasets Book Description Deep learning is a subset of machine learning where datasets with several layers of complexity can be processed. Hands-On Deep Learning with Apache Spark addresses the sheer complexity of technical and analytical parts and the speed at which deep learning solutions can be implemented on Apache Spark. The book starts with the fundamentals of Apache Spark and deep learning. You will set up Spark for deep learning, learn principles of distributed modeling, and understand different types of neural nets. You will then implement deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) on Spark. As you progress through the book, you will gain hands-on experience of what it takes to understand the complex datasets you are dealing with. During the course of this book, you will use popular deep learning frameworks, such as TensorFlow, Deeplearning4j, and Keras to train your distributed models. By the end of this book, you'll have gained experience with the implementation of your models on a variety of use cases. What you will learn * Understand the basics of deep learning * Set up Apache Spark for deep learning * Understand the principles of distribution modeling and different types of neural networks * Obtain an understanding of deep learning algorithms * Discover textual analysis and deep learning with Spark * Use popular deep learning frameworks, such as Deeplearning4j, TensorFlow, and Keras * Explore popular deep learning algorithms Who this book is for If you are a Scala developer, data scientist, or data analyst who wants to learn how to use Spark for implementing efficient deep learning models, Hands-On Deep Learning with Apache Spark is for you. Knowledge of the core machine learning concepts and some exposure to Spark will be helpful.

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

86 recipes on how to build fast, scalable, and powerful web services and applications with Go About This Book ? Become proficient in RESTful web services ? Build scalable, high-performant web applications in Go ? Get acquainted with Go frameworks for web development Who This Book Is For This book is for Go developers interested in learning how to use Go to build powerful web applications. A background in web development is expected. What You Will Learn ? Create a simple HTTP and TCP web server and understand how it works ? Explore record in a MySQL and MongoDB database ? Write and consume RESTful web service in Go ? Invent microservices in Go using Micro – a microservice toolkit ? Create and Deploy the Beego application with Nginx ? Deploy Go web application and Docker containers on an AWS EC2 instance In Detail Go is an open source programming language that is designed to scale and support concurrency at the language level. This gives you the liberty to write large concurrent web applications with ease. From creating web application to deploying them on Amazon Cloud Services, this book will be your one-stop guide to learn web development in Go. The Go Web Development Cookbook teaches you how to create REST services, write microservices, and deploy Go Docker containers. Whether you are new to programming or a professional developer, this book will help get you up to speed with web development in Go. We will focus on writing modular code in Go; in-depth informative examples build the base, one step at a time. You will learn how to create a server, work with static files, SQL, NoSQL databases, and Beego. You will also learn how to create and secure REST services, and create and deploy Go web application and Go Docker containers on Amazon Cloud Services. By the end of the book, you will be able to apply the skills you've gained in Go to create and explore web applications in any domain. Style and approach This book helps you learn core Go concepts faster by taking a recipe-based approach.

Create clean code with Dependency Injection principles About This Book ? Use DI to make your code loosely coupled to manage and test your applications easily on Spring 5 and Google Guice ? Learn the best practices and methodologies to implement DI ? Write more maintainable Java code by decoupling your objects from their implementations Who This Book Is For This book is for Java developers who would like to implement DI in their application. Prior knowledge of the Spring and Guice frameworks and Java programming is assumed. What You Will Learn ? Understand the benefits of DI and fo from a tightly coupled design to a cleaner design organized around dependencies ? See Java 9’s new features and modular framework ? Set up Guice and Spring in an application so that it can be used for DI ? Write integration tests for DI applications ? Use scopes to handle complex application scenarios ? Integrate any third-party library in your DI-enabled application ? Implement Aspect-Oriented Programming to handle common cross-cutting concerns such as logging, authentication, and transactions ? Understand IoC patterns and anti-patterns in DI In Detail Dependency Injection (DI) is a design pattern that allows us to remove the hard-coded dependencies and make our application loosely coupled, extendable, and maintainable. We can implement DI to move the dependency resolution from compile-time to runtime. This book will be your one stop guide to write loosely coupled code using the latest features of Java 9 with frameworks such as Spring 5 and Google Guice. We begin by explaining what DI is and teaching you about IoC containers. Then you’ll learn about object compositions and their role in DI. You’ll find out how to build a modular application and learn how to use DI to focus your efforts on the business logic unique to your application and let the framework handle the infrastructure work to put it all together. Moving on, you’ll gain knowledge of Java 9’s new features and modular framework and how DI works in Java 9. Next, we’ll explore Spring and Guice, the popular frameworks for DI. You’ll see how to define injection keys and configure them at the framework-specific level. After that, you’ll find out about the different types of scopes available in both popular frameworks. You’ll see how to manage dependency of cross-cutting concerns while writing applications through aspect-oriented programming. Towards the end, you’ll learn to integrate any third-party library in your DI-enabled application and explore common pitfalls and recommendations to build a solid application with the help of best practices, patterns, and anti-patterns in DI. Style and approach This book will take an easy-to-understand, step-by-step approach providing hands-on examples at every stage.

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

Create visually appealing and feature-rich applications by using Qt 5 and the C++ language About This Book ? Explore Qt 5’s powerful features to easily design your GUI application ? Leverage Qt 5 to build attractive cross-platform applications ? Work with Qt modules for multimedia, networking, and location, to customize your Qt applications Who This Book Is For This book will appeal to developers and programmers who would like to build GUI-based applications. Basic knowledge of C++ is necessary and the basics of Qt would be helpful. What You Will Learn ? Implement tools provided by Qt 5 to design a beautiful GUI ? Understand different types of graphs and charts supported by Qt 5 ? Create a web browser using the Qt 5 WebEngine module and web view widget ? Connect to the MySQL database and display data obtained from it onto the Qt 5 GUI ? Incorporate the Qt 5 multimedia and networking module in your application ? Develop Google Map-like applications using Qt 5’s location module ? Discover cross-platform development by exporting the Qt 5 application to different platforms ? Uncover the secrets behind debugging Qt 5 and C++ applications In Detail Qt 5, the latest version of Qt, enables you to develop applications with complex user interfaces for multiple targets. It provides you with faster and smarter ways to create modern UIs and applications for multiple platforms. This book will teach you to design and build graphical user interfaces that are functional, appealing, and user-friendly. In the initial part of the book, you will learn what Qt 5 is and what you can do with it. You will explore the Qt Designer, discover the different types of widgets generally used in Qt 5, and then connect your application to the database to perform dynamic operations. Next, you will be introduced to Qt 5 chart which allows you to easily render different types of graphs and charts and incorporate List View Widgets in your application. You will also work with various Qt modules, like QtLocation, QtWebEngine, and the networking module through the course of the book. Finally, we will focus on cross-platform development with QT 5 that enables you to code once and run it everywhere, including mobile platforms. By the end of this book, you will have successfully learned about high-end GUI applications and will be capable of building many more powerful, cross-platform applications. Style and approach This is a comprehensive guide that explores the essential Qt features and implement them in building real-world cross-platform GUI applications

Create classic data structures and algorithms such as depth-first search and breadth-first search, learn recursion, as well as create and use a heap data structure using JavaScript About This Book ? Implement common data structures and the associated algorithms along with the context in which they are used ? Master existing JavaScript data structures such as arrays, sets, and maps, and learn how to implement new ones such as stacks, linked lists, trees, and graphs in ES 8 ? Develop abstract data types to make JavaScript a more flexible and powerful programming language Who This Book Is For If you’re a JavaScript developer who wants to dive deep into JavaScript and write complex programs using JavaScript data structures and algorithms, this book is for you. What You Will Learn ? Declare, initialize, add, and remove items from arrays, stacks, and queues ? Create and use linked lists, doubly linked lists, and circular linked lists ? Store unique elements with hash tables, dictionaries, and sets ? Explore the use of binary trees and binary search trees ? Sort data structures using algorithms such as bubble sort, selection sort, insertion sort, merge sort, and quick sort ? Search elements in data structures using sequential sort and binary search In Detail A data structure is a particular way of organizing data in a computer to utilize resources efficiently. Data structures and algorithms are the base of every solution to any programming problem. With this book, you will learn to write complex and powerful code using the latest ES 2017 features. Learning JavaScript Data Structures and Algorithms begins by covering the basics of JavaScript and introduces you to ECMAScript 2017, before gradually moving on to the most important data structures such as arrays, queues, stacks, and linked lists. You will gain in-depth knowledge of how hash tables and set data structures function as well as how trees and hash maps can be used to search files in an HD or represent a database. This book serves as a route to take you deeper into JavaScript. You’ll also get a greater understanding of why and how graphs, one of the most complex data structures, are largely used in GPS navigation systems in social networks. Toward the end of the book, you’ll discover how all the theories presented in this book can be applied to solve real-world problems while working on your own computer networks and Facebook searches. Style and approach Easy to follow guide which will cover the most used data structures and sorting/searching algorithms known in the computer science world along with examples to help the readers understand each chapter thoroughly.

Master Game UI system by creating captivating user interface components with Unity 5 through Unity 2018 and C#. Learn about UI texts, images, world space UI, mobile-specific UI and much more. About This Book ? Develop a game UI with both technical and aesthetic considerations ? Use all the UI elements provided by Unity's UI system ? Step-by-step examples of creating user interface components in the top game genres Who This Book Is For This book is for anyone keen to improve their games via a great user interface with Unity's UI system. If you're looking for a book that explains how to develop specific user interfaces or that thoroughly explains how each of the individual Unity components work, this book is for you. What You Will Learn ? Design principles and patterns for laying out elements in your UI ? Techniques that allow your UI to scale appropriately in different resolutions ? How to use automatic layouts to streamline your UI building process ? Properties of the Event System and how to appropriately hook events to your UI elements ? Access the components and properties of UI elements via code ? Implement all of Unity's built-in UI elements as well as those provided by TextMeshPro ? Develop key UI components that are popularly used in multiple game genres ? Add visual flare to user interfaces with the use of animation and particle effects ? Create a UI that displays in the Screen Space as well as World Space In Detail A functional UI is an important component for player interaction in every type of video game. Along with imparting crucial statistical information to the player, the UI is also the window through which the player engages with the world established by the game. Unity's tools give you the opportunity to create complex and attractive UIs to make your game stand out. This book helps you realize the full potential of Unity's powerful tools to create the best UI for your games by walking you through the creation of myriad user interface components. Learn how to create visually engaging heads-up-displays, pause menus, health bars, circular progress bars, animated menus, and more. This book not only teaches how to lay out visual elements, but also how to program these features and implement them across multiple games of varying genres. While working through the examples provided, you will learn how to develop a UI that scales to multiple screen resolutions, so your game can be released on multiple platforms with minimal changes. Style and approach The book walks you through the process of creating many different user interface components, by describing each UI component and property thoroughly and then providing step-by-step examples of its implementation. You will not only learn how to lay out visual elements, but you will also learn how to program for these features and hook them in to your game. The examples provided in the book can be reused for many other products.

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.

Recipe-based approach to tackle the most common problems in Computer Vision by leveraging the functionality of OpenCV using Python APIs About This Book ? Build computer vision applications with OpenCV functionality via Python API ? Get to grips with image processing, multiple view geometry, and machine learning ? Learn to use deep learning models for image classification, object detection, and face recognition Who This Book Is For This book is for developers who have a basic knowledge of Python. If you are aware of the basics of OpenCV and are ready to build computer vision systems that are smarter, faster, more complex, and more practical than the competition, then this book is for you. What You Will Learn ? Get familiar with low-level image processing methods ? See the common linear algebra tools needed in computer vision ? Work with different camera models and epipolar geometry ? Find out how to detect interesting points in images and compare them ? Binarize images and mask out regions of interest ? Detect objects and track them in videos In Detail OpenCV 3 is a native cross-platform library for computer vision, machine learning, and image processing. OpenCV's convenient high-level APIs hide very powerful internals designed for computational efficiency that can take advantage of multicore and GPU processing. This book will help you tackle increasingly challenging computer vision problems by providing a number of recipes that you can use to improve your applications. In this book, you will learn how to process an image by manipulating pixels and analyze an image using histograms. Then, we'll show you how to apply image filters to enhance image content and exploit the image geometry in order to relay different views of a pictured scene. We’ll explore techniques to achieve camera calibration and perform a multiple-view analysis. Later, you’ll work on reconstructing a 3D scene from images, converting low-level pixel information to high-level concepts for applications such as object detection and recognition. You’ll also discover how to process video from files or cameras and how to detect and track moving objects. Finally, you'll get acquainted with recent approaches in deep learning and neural networks. By the end of the book, you’ll be able to apply your skills in OpenCV to create computer vision applications in various domains. Style and approach This book helps you learn the core concepts of OpenCV faster by taking a recipe-based approach where you can try out different code snippets to understand a concept.

Key concepts, sample applications, best practices, and troubleshooting tips to build highly scalable applications in AWS. About This Book ? Design highly available, cost efficient, fault tolerant, and scalable distributed systems ? A practical guide that will help you build, deploy, and manage applications with ease. ? Develop effective solutions with AWS SDK and Lambda Who This Book Is For This book targets developers who would like to build and manage web and mobile applications and services on the AWS platform. If you are an architect you will be able to take a deep dive and use examples that can be readily applied to real world scenarios. Some prior programming experience is assumed along with familiarity of cloud computing. What You Will Learn ? Learn how to get up and running with AWS Developer Tools. ? Integrate the four major phases in the Release Processes. Source, Build, Test and Production. ? Learn how to integrate Continuous Integration, Continuous Delivery, and Continuous Deployment in AWS. ? Make secure, scalable and fault tolerant applications. ? Understand different architectures and deploy complex architectures within minutes In Detail Continuous deployment and Agile methodology have enabled huge advances in modern applications. This book will enable the reader to make use of this rapidly evolving technology to build highly scalable applications within AWS using different architectures. You will begin with installation of AWS SDK and you will get hands-on experience on creating an application using AWS Management Console and AWS Command Line Interface (CLI). Next you will be integrating Applications with AWS services such as DynamoDB, Amazon Kinesis, AWS Lambda, Amazon SQS and Amazon SWF Following this you will get well versed with CI/CD workflow and work with four major phases in Release processes – Source, Build, Test and Production. Next you will learn to apply AWS developer tools in your Continuous Integration (CI) and Continuous Deployment (CD) WorkFlow. Later you will learn about User Authentication using Amazon Cognito and also how you can evaluate the best architecture as per your infrastructure costs. You will learn about Amazon EC2 service and deploy an app using Amazon EC2.You will also get well versed with container service which is Amazon EC2 Container Service (Amazon ECS) and you will learn to deploy an app using Amazon ECS. Along with EC2 and ECS, you will also deploying a practical real-world example of a CI/CD application with the Serverless Application Framework which is known as AWS Lambda. Finally you will learn how to build, develop and deploy the Application using AWS Developer tools like AWS CodeCommit, AWS CodeBuild, AWS CodeDeploy and AWS CodePipeline as per project needs. Also you can develop and deploy applications within minutes using AWS CodeStar from wizard. By the end of this book, the reader will effectively build, deploy, and manage applications on AWS along with scaling and securing applications with best practices and troubleshooting tips. Style and approach This book covers follows an approach where you will learn the key concepts followed by a real world example and some tips and tricks to make building and deploying easier

Explore and master the most important algorithms for solving complex machine learning problems. About This Book ? Discover high-performing machine learning algorithms and understand how they work in depth. ? One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and their implementation. ? Master concepts related to algorithm tuning, parameter optimization, and more Who This Book Is For This book is an ideal and relevant source of content for data science professionals who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. A basic knowledge of machine learning is preferred to get the best out of this guide. What You Will Learn ? Explore how a ML model can be trained, optimized, and evaluated ? Understand how to create and learn static and dynamic probabilistic models ? Successfully cluster high-dimensional data and evaluate model accuracy ? Discover how artificial neural networks work and how to train, optimize, and validate them ? Work with Autoencoders and Generative Adversarial Networks ? Apply label spreading and propagation to large datasets ? Explore the most important Reinforcement Learning techniques In Detail Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour. Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries such as scikit-learn. You will also learn how to use Keras and TensorFlow to train effective neural networks. If you are looking for a single resource to study, implement, and solve end-to-end machine learning problems and use-cases, this is the book you need. Style and approach A hands-on guide filled with real-world examples of popular algorithms used for data science and machine learning

Unleash the power of MERN stack by building diverse web applications using React, Node.js, Express, and MongoDB About This Book ? Create dynamic web applications with the MERN stack ? Leverage the power of React in building interactive and complex user interfaces ? Unlock the potential of Node, Express, and MongoDB to build modern full-stack applications Who This Book Is For Full-Stack React Web Development Projects is for JavaScript developers who have some experience with React, but no previous experience with full-stack development involving Node, Express, and MongoDB, and who want practical guidelines to start building different types of real-world web applications with this stack. What You Will Learn ? Set up your development environment and develop a MERN application ? Implement user authentication and authorization using JSON Web Tokens ? Build a social media application by extending the basic MERN application ? Create an online marketplace application with shopping cart and Stripe payments ? Develop a media streaming application using MongoDB GridFS ? Implement server-side rendering with data to improve SEO ? Set up and use React 360 to develop user interfaces with VR capabilities ? Learn industry best practices to make MERN stack applications reliable and scalable In Detail The benefits of using a full JavaScript stack for web development are undeniable, especially when robust and widely adopted technologies such as React, Node, and Express and are available. Combining the power of React with industry-tested, server-side technologies, such as Node, Express, and MongoDB, creates a diverse array of possibilities when developing real-world web applications. This book guides you through preparing the development environment for MERN stack-based web development, to creating a basic skeleton application and extending it to build four different web applications. These applications include a social media, an online marketplace, a media streaming, and a web-based game application with virtual reality features. While learning to set up the stack and developing a diverse range of applications with this book, you will grasp the inner workings of the MERN stack, extend its capabilities for complex features, and gain actionable knowledge of how to prepare MERN-based applications to meet the growing demands of real-world web applications. Style and approach This book provides practical guidelines on setting up and building MERN stack based applications, while providing further explanations on key concepts and implementations.

Explore the Rust Standard library and compose algorithms with minimal dependency on external libraries About This Book ? Develop high-quality, fast, and portable applications by leveraging the power of Rust's Standard library. ? Practical recipes that will help you work with the Standard library to boost your productivity as a Rust developer. ? Learn about most relevant external crates to be used along with the Standard library. Who This Book Is For This book is for developers who would like to explore the power of Rust and learn to use the STL for various functionalities. A basic Rust programming knowledge is assumed. What You Will Learn ? How to use the basic modules of the library: strings, command line access, and more. ? Implement collections and folding of collections using vectors, Deque, linked lists, and more. ? Handle various file types , compressing and decompressing data. ? Search for files with glob patterns. ? Implement parsing through various formats such as CSV, TOML, and JSON. ? Utilize drop trait , the Rust version of destructor. ? Resource locking with Bilocks. In Detail Mozilla’s Rust is gaining much attention with amazing features and a powerful library. This book will take you through varied recipes to teach you how to leverage the Standard library to implement efficient solutions. The book begins with a brief look at the basic modules of the Standard library and collections. From here, the recipes will cover packages that support file/directory handling and interaction through parsing. You will learn about packages related to advanced data structures, error handling, and networking. You will also learn to work with futures and experimental nightly features. The book also covers the most relevant external crates in Rust. By the end of the book, you will be proficient at using the Rust Standard library. Style and approach This recipe-based practical guide presents each topic with step-by-step instructions on how you can create fast and efficient applications utilizing Rust's Standard library packages.

Simplify next-generation deep learning by implementing powerful generative models using Python, TensorFlow and Keras Key Features *Understand the common architecture of different types of GANs *Train, optimize, and deploy GAN applications using TensorFlow and Keras *Build generative models with real-world data sets, including 2D and 3D data Book Description Developing Generative Adversarial Networks (GANs) is a complex task, and it is often hard to find code that is easy to understand. This book leads you through eight different examples of modern GAN implementations, including CycleGAN, simGAN, DCGAN, and 2D image to 3D model generation. Each chapter contains useful recipes to build on a common architecture in Python, TensorFlow and Keras to explore increasingly difficult GAN architectures in an easy-to-read format. The book starts by covering the different types of GAN architecture to help you understand how the model works. This book also contains intuitive recipes to help you work with use cases involving DCGAN, Pix2Pix, and so on. To understand these complex applications, you will take different real-world data sets and put them to use. By the end of this book, you will be equipped to deal with the challenges and issues that you may face while working with GAN models, thanks to easy-to-follow code solutions that you can implement right away. What you will learn *Structure a GAN architecture in pseudocode *Understand the common architecture for each of the GAN models you will build *Implement different GAN architectures in TensorFlow and Keras *Use different datasets to enable neural network functionality in GAN models *Combine different GAN models and learn how to fine-tune them *Produce a model that can take 2D images and produce 3D models *Develop a GAN to do style transfer with Pix2Pix Who this book is for This book is for data scientists, machine learning developers, and deep learning practitioners looking for a quick reference to tackle challenges and tasks in the GAN domain. Familiarity with machine learning concepts and working knowledge of Python programming language will help you get the most out of the book.

A comprehensive guide in developing and deploying high performance microservices with Rust Key Features * Start your microservices journey and get a broader perspective on microservices development using RUST 2018, * Build, deploy, and test microservices using AWS * Explore advanced techniques for developing microservices such as actor model, Requests Routing, and threads Book Description Microservice architecture is sweeping the world as the de facto pattern for building web-based applications. Rust is a language particularly well-suited for building microservices. It is a new system programming language that offers a practical and safe alternative to C. This book describes web development using the Rust programming language and will get you up and running with modern web frameworks and crates with examples of RESTful microservices creation. You will deep dive into Reactive programming, and asynchronous programming, and split your web application into a set of concurrent actors. The book provides several HTTP-handling examples with manageable memory allocations. You will walk through stateless high-performance microservices, which are ideally suitable for computation or caching tasks, and look at stateful microservices, which are filled with persistent data and database interactions. As we move along, you will learn how to use Rust macros to describe business or protocol entities of our application and compile them into native structs, which will be performed at full speed with the help of the server's CPU. Finally, you will be taken through examples of how to test and debug microservices and pack them into a tiny monolithic binary or put them into a container and deploy them to modern cloud platforms such as AWS. What you will learn * Get acquainted with leveraging Rust web programming * Get to grips with various Rust crates, such as hyper, Tokio, and Actix * Explore RESTful microservices with Rust * Understand how to pack Rust code to a container using Docker * Familiarize yourself with Reactive microservices * Deploy your microservices to modern cloud platforms such as AWS Who this book is for This book is for developers who have basic knowledge of RUST, and want to learn how to build, test, scale, and manage RUST microservices. No prior experience of writing microservices in RUST is assumed.

Grasp advanced PowerShell Core 6.0 functionalities to automate your environment Key Features * Keep up with changes introduced in PowerShell Core 6.0 * Easily maintain appropriate compatibility with older versions * Automate complex tasks, manipulate data, and secure your environment with PowerShell Core 6.0 Book Description PowerShell scripts offer a handy way to automate various chores, however working effectively with these scripts can be a difficult task. This comprehensive guide starts with the fundamentals before moving on to advanced-level topics to help you become a PowerShell Core 6.0 expert. The first module, PowerShell Core 6.0 Fundamentals, begins with the new features of PowerShell Core 6.0, installing it on Linux, and working with parameters, objects and .NET classes from within PowerShell Core 6.0. As you make your way through the chapters, you'll see how to efficiently manage large amounts of data and interact with other services using PowerShell Core 6.0. You'll be able to make the most of PowerShell Core 6.0's powerful automation feature, where you will have different methods available to parse data and manipulate regular expressions and Windows Management Instrumentation (WMI). After having explored automation, you will enter the extending PowerShell Core 6.0 module, covering asynchronous processing and desired state configuration. In the last module, you will learn to extend PowerShell Core 6.0 using advanced scripts and filters, and also debug issues along with working on error handling techniques. By the end of this book, you will be an expert in scripting with PowerShell Core 6.0. What you will learn * Optimize code through the use of functions, switches, and looping structures * Work with objects and operators to test and manipulate data * Parse and manipulate different data types * Create scripts and functions using PowerShell * Use jobs, events, and popular public modules which assist with implementing multithreading * Write .NET classes with ease within the PowerShell * Create and implement regular expressions in PowerShell scripts * Make use of advanced techniques to define and restrict the behavior of parameters Who this book is for If you are a system administrator who wants to become an expert in controlling and automating your Windows environment, then Mastering Windows PowerShell Scripting is for you. It is also ideal for those new to the PowerShell language.

Discover the skill-sets required to implement various approaches to Machine Learning with Python Key Features * Explore unsupervised learning with clustering, autoencoders, restricted Boltzmann machines, and more * Build your own neural network models using modern Python libraries * Practical examples show you how to implement different machine learning and deep learning techniques Book Description Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to cluster large sets of data and analyze them repeatedly until the desired outcome is found using Python. This book starts with the key differences between supervised, unsupervised, and semi-supervised learning. You will be introduced to the best-used libraries and frameworks from the Python ecosystem and address unsupervised learning in both the machine learning and deep learning domains. You will explore various algorithms, techniques that are used to implement unsupervised learning in real-world use cases. You will learn a variety of unsupervised learning approaches, including randomized optimization, clustering, feature selection and transformation, and information theory. You will get hands-on experience with how neural networks can be employed in unsupervised scenarios. You will also explore the steps involved in building and training a GAN in order to process images. By the end of this book, you will have learned the art of unsupervised learning for different real-world challenges. What you will learn * Use cluster algorithms to identify and optimize natural groups of data * Explore advanced non-linear and hierarchical clustering in action * Soft label assignments for fuzzy c-means and Gaussian mixture models * Detect anomalies through density estimation * Perform principal component analysis using neural network models * Create unsupervised models using GANs Who this book is for This book is intended for statisticians, data scientists, machine learning developers, and deep learning practitioners who want to build smart applications by implementing key building block unsupervised learning, and master all the new techniques and algorithms offered in machine learning and deep learning using real-world examples. Some prior knowledge of machine learning concepts and statistics is desirable.