Discover the power of functional programming, lazy evaluation, monads, concurrency, and immutability to create succinct and expressive implementations Key Features * Get a solid understanding of how to apply functional programming concepts in TypeScript * Explore TypeScript runtime features such as event loop, closures, and Prototypes * Gain deeper knowledge on the pros and cons of TypeScript Book Description Functional programming is a powerful programming paradigm that can help you to write better code. However, learning functional programming can be complicated, and the existing literature is often too complex for beginners. This book is an approachable introduction to functional programming and reactive programming with TypeScript for readers without previous experience in functional programming with JavaScript, TypeScript , or any other programming language. The book will help you understand the pros, cons, and core principles of functional programming in TypeScript. It will explain higher order functions, referential transparency, functional composition, and monads with the help of effective code examples. Using TypeScript as a functional programming language, you’ll also be able to brush up on your knowledge of applying functional programming techniques, including currying, laziness, and immutability, to real-world scenarios. By the end of this book, you will be confident when it comes to using core functional and reactive programming techniques to help you build effective applications with TypeScript. What you will learn * Understand the pros and cons of functional programming * Delve into the principles, patterns, and best practices of functional and reactive programming * Use lazy evaluation to improve the performance of applications * Explore functional optics with Ramda * Gain insights into category theory functional data structures such as Functors and Monads * Use functions as values, so that they can be passed as arguments to other functions Who this book is for This book is designed for readers with no prior experience of functional programming with JavaScript, TypeScript or any other programming language. Some familiarity with TypeScript and web development is a must to grasp the concepts in the book easily.

Leverage the features and libraries of Python to administrate your environment efficiently. Key Features * Learn how to solve problems of system administrators and automate routine activities * Learn to handle regular expressions, network administration * Building GUI, web-scraping and database administration including data analytics Book Description Python has evolved over time and extended its features in relation to every possible IT operation. Python is simple to learn, yet has powerful libraries that can be used to build powerful Python scripts for solving real-world problems and automating administrators' routine activities. The objective of this book is to walk through a series of projects that will teach readers Python scripting with each project. This book will initially cover Python installation and quickly revise basic to advanced programming fundamentals. The book will then focus on the development process as a whole, from setup to planning to building different tools. It will include IT administrators' routine activities (text processing, regular expressions, file archiving, and encryption), network administration (socket programming, email handling, the remote controlling of devices using telnet/ssh, and protocols such as SNMP/DHCP), building graphical user interface, working with websites (Apache log file processing, SOAP and REST APIs communication, and web scraping), and database administration (MySQL and similar database data administration, data analytics, and reporting). By the end of this book, you will be able to use the latest features of Python and be able to build powerful tools that will solve challenging, real-world tasks What you will learn * Understand how to install Python and debug Python scripts * Understand and write scripts for automating testing and routine administrative activities * Understand how to write scripts for text processing, encryption, decryption, and archiving * Handle files, such as pdf, excel, csv, and txt files, and generate reports * Write scripts for remote network administration, including handling emails * Build interactive tools using a graphical user interface * Handle Apache log files, SOAP and REST APIs communication * Automate database administration and perform statistical analysis Who this book is for This book would be ideal for users with some basic understanding of Python programming and who are interested in scaling their programming skills to command line scripting and system administration. Prior knowledge of Python would be necessary.

Build efficient and fast Qt applications, target performance problems, and discover solutions to refine your code Key Features * Build efficient and concurrent applications in Qt to create cross-platform applications * Identify performance bottlenecks and apply the correct algorithm to improve application performance * Delve into parallel programming and memory management to optimize your code Book Description Achieving efficient code through performance tuning is one of the key challenges faced by many programmers. This book looks at Qt programming from a performance perspective. You'll explore the performance problems encountered when using the Qt framework and means and ways to resolve them and optimize performance. The book highlights performance improvements and new features released in Qt 5.9, Qt 5.11, and 5.12 (LTE). You'll master general computer performance best practices and tools, which can help you identify the reasons behind low performance, and the most common performance pitfalls experienced when using the Qt framework. In the following chapters, you’ll explore multithreading and asynchronous programming with C++ and Qt and learn the importance and efficient use of data structures. You'll also get the opportunity to work through techniques such as memory management and design guidelines, which are essential to improve application performance. Comprehensive sections that cover all these concepts will prepare you for gaining hands-on experience of some of Qt's most exciting application fields - the mobile and embedded development domains. By the end of this book, you'll be ready to build Qt applications that are more efficient, concurrent, and performance-oriented in nature What you will learn * Understand classic performance best practices * Get to grips with modern hardware architecture and its performance impact * Implement tools and procedures used in performance optimization * Grasp Qt-specific work techniques for graphical user interface (GUI) and platform programming * Make Transmission Control Protocol (TCP) and Hypertext Transfer Protocol (HTTP) performant and use the relevant Qt classes * Discover the improvements Qt 5.9 (and the upcoming versions) holds in store * Explore Qt's graphic engine architecture, strengths, and weaknesses Who this book is for This book is designed for Qt developers who wish to build highly performance applications for desktop and embedded devices. Programming Experience with C++ is required.

Equip yourself with the most complete and comprehensive preparation experience for Identity with Windows Server 2016: Microsoft 70-742 exam. Key Features * Helps you demonstrate real-world mastery of Windows Server 2016 identity features and functionality and prepare for 70-742 * Acquire skills to reduce IT costs and deliver more business value * Enhance your existing skills through practice questions and mock tests Book Description MCSA: Windows Server 2016 certification is one of the most sought-after certifications for IT professionals, which includes working with Windows Server and performing administrative tasks around it. This book is aimed at the 70-742 certification and is part of Packt's three-book series on MCSA Windows Server 2016 certification, which covers Exam 70-740, Exam 70-741, and Exam 70-742. This exam guide covers the exam objectives for the 70-742 Identity with Windows Server 2016 exam. It starts with installing and configuring Active Directory Domain Services (AD DS), managing and maintaining AD DS objects and advanced configurations, configuring Group Policy, Active Directory Certificate Services, and Active Directory Federation Services and Rights Management. At the end of each chapter, convenient test questions will help you in preparing for the certification in a practical manner. By the end of this book, you will be able to develop the knowledge and skills needed to complete MCSA Exam 70-742: Identity with Windows Server 2016 with confidence. What you will learn * Install, configure, and maintain Active Directory Domain Services (AD DS) * Manage Active Directory Domain Services objects * Configure and manage Active Directory Certificate Services * Configure and manage Group Policy * Design, implement, and configure Active Directory Federation Services * Implement and configure Active Directory Rights Management Services Who this book is for This book primarily targets system administrators who are looking to gain knowledge about identity and access technologies with Windows Server 2016 and aiming to pass the 70-742 certification. This will also help infrastructure administrators who are looking to gain advanced knowledge and understanding of identity and access technologies with Windows Server 2016. Familiarity with the concepts such as Active Directory, DNS is assumed.

Learn best practices for testing with Jira and model industry workflows that can be used during the software development lifecycle Key Features * Integrate Jira with test management tools such as Zephyr, Test Management, and SynapseRT * Understand test case management, traceability, and test execution with reports * Implement continuous integration using Jira, Jenkins, and automated testing tools Book Description Hands-On Test Management with Jira begins by introducing you to the basic concepts of Jira and takes you through real-world software testing processes followed by various organizations. As you progress through the chapters, the book explores and compares the three most popular Jira plugins—Zephyr, Test Management, and synapseRT. With this book, you’ll gain a practical understanding of test management processes using Jira. You’ll learn how to create and manage projects, create Jira tickets to manage customer requirements, and track Jira tickets. You’ll also understand how to develop test plans, test cases, and test suites, and create defects and requirement traceability matrices, as well as generating reports in Jira. Toward the end, you’ll understand how Jira can help the SQA teams to use the DevOps pipeline for automating execution and managing test cases. You’ll get to grips with configuring Jira with Jenkins to execute automated test cases in Selenium. By the end of this book, you’ll have gained a clear understanding of how to model and implement test management processes using Jira. What you will learn * Understand QMS to effectively implement quality systems in your organization * Explore a business-driven structured approach to Test Management using TMap NEXT * Implement different aspects of test planning, test strategy, and test execution * Organize and manage Agile projects in Scrum and Kanban * Uncover Jira plugins available in the Atlassian Marketplace for testing and project management * Configure a DevOps pipeline for continuous integration using Jira with Jenkins Who this book is for If you’re a quality assurance professional, software project manager, or test manager interested in learning test management best practices in your team or organization, this book is for you. Prior knowledge of test management and Jenkins will be beneficial in understanding the concepts covered in this book.

Demystify the complexity of machine learning techniques and create evolving, clever solutions to solve your problems Key Features *Master supervised, unsupervised, and semi-supervised ML algorithms and their implementation *Build deep learning models for object detection, image classification, similarity learning, and more *Build, deploy, and scale end-to-end deep neural network models in a production environment Book Description This Learning Path is your complete guide to quickly getting to grips with popular machine learning algorithms. You'll be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this Learning Path will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries. You'll bring the use of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Next, you'll learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF clusters, deploy production models with TensorFlow Serving. You'll implement different techniques related to object classification, object detection, image segmentation, and more. By the end of this Learning Path, you'll have obtained in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problems This Learning Path includes content from the following Packt products: *Mastering Machine Learning Algorithms by Giuseppe Bonaccorso *Mastering TensorFlow 1.x by Armando Fandango *Deep Learning for Computer Vision by Rajalingappaa Shanmugamani What you will learn *Explore how an ML model can be trained, optimized, and evaluated *Work with Autoencoders and Generative Adversarial Networks *Explore the most important Reinforcement Learning techniques *Build end-to-end deep learning (CNN, RNN, and Autoencoders) models Who this book is for This Learning Path is for data scientists, machine learning engineers, artificial intelligence engineers who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. You will encounter the advanced intricacies and complex use cases of deep learning and AI. A basic knowledge of programming in Python and some understanding of machine learning concepts are required to get the best out of this Learning Path.

Implement machine learning algorithms to build ensemble models using Keras, H2O, Scikit-Learn, Pandas and more Key Features * Apply popular machine learning algorithms using a recipe-based approach * Implement boosting, bagging, and stacking ensemble methods to improve machine learning models * Discover real-world ensemble applications and encounter complex challenges in Kaggle competitions Book Description Ensemble modeling is an approach used to improve the performance of machine learning models. It combines two or more similar or dissimilar machine learning algorithms to deliver superior intellectual powers. This book will help you to implement popular machine learning algorithms to cover different paradigms of ensemble machine learning such as boosting, bagging, and stacking. The Ensemble Machine Learning Cookbook will start by getting you acquainted with the basics of ensemble techniques and exploratory data analysis. You'll then learn to implement tasks related to statistical and machine learning algorithms to understand the ensemble of multiple heterogeneous algorithms. It will also ensure that you don't miss out on key topics, such as like resampling methods. As you progress, you’ll get a better understanding of bagging, boosting, stacking, and working with the Random Forest algorithm using real-world examples. The book will highlight how these ensemble methods use multiple models to improve machine learning results, as compared to a single model. In the concluding chapters, you'll delve into advanced ensemble models using neural networks, natural language processing, and more. You’ll also be able to implement models such as fraud detection, text categorization, and sentiment analysis. By the end of this book, you'll be able to harness ensemble techniques and the working mechanisms of machine learning algorithms to build intelligent models using individual recipes. What you will learn * Understand how to use machine learning algorithms for regression and classification problems * Implement ensemble techniques such as averaging, weighted averaging, and max-voting * Get to grips with advanced ensemble methods, such as bootstrapping, bagging, and stacking * Use Random Forest for tasks such as classification and regression * Implement an ensemble of homogeneous and heterogeneous machine learning algorithms * Learn and implement various boosting techniques, such as AdaBoost, Gradient Boosting Machine, and XGBoost Who this book is for This book is designed for data scientists, machine learning developers, and deep learning enthusiasts who want to delve into machine learning algorithms to build powerful ensemble models. Working knowledge of Python programming and basic statistics is a must to help you grasp the concepts in the book.

Leverage powerful features of the SQL Server and watch your infrastructure transform into a high-performing, reliable network of systems. Key Features * Explore more than 20 real-world use cases to understand SQL Server features * Get to grips with the SQL Server Always On technology * Learn how to choose HA and DR topologies for your system Book Description Professional SQL Server High Availability and Disaster Recovery explains the high availability and disaster recovery technologies available in SQL Server: Replication, AlwaysOn, and Log Shipping. You’ll learn what they are, how to monitor them, and how to troubleshoot any related problems. You will be introduced to the availability groups of AlwaysOn and learn how to configure them to extend your database mirroring. Through this book, you will be able to explore the technical implementations of high availability and disaster recovery technologies that you can use when you create a highly available infrastructure, including hybrid topologies. By the end of the book, you’ll be equipped with all that you need to know to develop robust and high performance infrastructure. What you will learn * Configure and troubleshoot Replication, AlwaysOn, and Log Shipping * Study the best practices to implement HA and DR solutions * Design HA and DR topologies for the SQL Server and study how to choose a topology for your environment * Use T-SQL to configure replication, AlwaysOn, and log shipping * Migrate from On-Premise SQL Server to Azure SQL Database * Manage and maintain AlwaysOn availability groups for extended database mirroring Who this book is for Professional SQL Server High Availability and Disaster Recovery is for you if you are a database administrator or database developer who wants to improve the performance of your production environment. Prior experience of working with SQL Server will help you get the most out of this book.

Create advanced data and integrated solutions using Azure Event Grid, functions, and containers Key Features * Get familiar with the different design patterns available in Microsoft Azure * Develop Azure cloud architecture and a pipeline management system * Get to know the security best practices for your Azure deployment Book Description Over the years, Azure cloud services have grown quickly, and the number of organizations adopting Azure for their cloud services is also gradually increasing. Leading industry giants are finding that Azure fulfills their extensive cloud requirements. Azure for Architects – Second Edition starts with an extensive introduction to major designing and architectural aspects available with Azure. These design patterns focus on different aspects of the cloud, such as high availability, security, and scalability. Gradually, we move on to other aspects, such as ARM template modular design and deployments. This is the age of microservices and serverless is the preferred implementation mechanism for them. This book covers the entire serverless stack available in Azure including Azure Event Grid, Azure Functions, and Azure Logic Apps. New and advance features like durable functions are discussed at length. A complete integration solution using these serverless technologies is also part of the book. A complete chapter discusses all possible options related to containers in Azure including Azure Kubernetes services, Azure Container Instances and Registry, and Web App for Containers. Data management and integration is an integral part of this book that discusses options for implementing OLTP solutions using Azure SQL, Big Data solutions using Azure Data factory and Data Lake Storage, eventing solutions using stream analytics, and Event Hubs. This book will provide insights into Azure governance features such as tagging, RBAC, cost management, and policies. By the end of this book, you will be able to develop a full-?edged Azure cloud solution that is Enterprise class and future-ready. What you will learn * Create an end-to-end integration solution using Azure Serverless Stack * Learn Big Data solutions and OLTP–based applications on Azure * Understand DevOps implementations using Azure DevOps * Architect solutions comprised of multiple resources in Azure * Develop modular ARM templates * Develop Governance on Azure using locks, RBAC, policies, tags and cost * Learn ways to build data solutions on Azure * Understand the various options related to containers including Azure Kubernetes Services Who this book is for If you are Cloud Architects, DevOps Engineers, or developers who want to learn key architectural aspects of the Azure Cloud platform, then this book is for you. Prior basic knowledge of the Azure Cloud platform is good to have.

Design, develop, and deploy innovative forensic solutions using Python Key Features * Discover how to develop Python scripts for effective digital forensic analysis * Master the skills of parsing complex data structures with Python libraries * Solve forensic challenges through the development of practical Python scripts Book Description Digital forensics plays an integral role in solving complex cybercrimes and helping organizations make sense of cybersecurity incidents. This second edition of Learning Python for Forensics illustrates how Python can be used to support these digital investigations and permits the examiner to automate the parsing of forensic artifacts to spend more time examining actionable data. The second edition of Learning Python for Forensics will illustrate how to develop Python scripts using an iterative design. Further, it demonstrates how to leverage the various built-in and community-sourced forensics scripts and libraries available for Python today. This book will help strengthen your analysis skills and efficiency as you creatively solve real-world problems through instruction-based tutorials. By the end of this book, you will build a collection of Python scripts capable of investigating an array of forensic artifacts and master the skills of extracting metadata and parsing complex data structures into actionable reports. Most importantly, you will have developed a foundation upon which to build as you continue to learn Python and enhance your efficacy as an investigator. What you will learn * Learn how to develop Python scripts to solve complex forensic problems * Build scripts using an iterative design * Design code to accommodate present and future hurdles * Leverage built-in and community-sourced libraries * Understand the best practices in forensic programming * Learn how to transform raw data into customized reports and visualizations * Create forensic frameworks to automate analysis of multiple forensic artifacts * Conduct effective and efficient investigations through programmatic processing Who this book is for If you are a forensics student, hobbyist, or professional seeking to increase your understanding in forensics through the use of a programming language, then Learning Python for Forensics is for you. You are not required to have previous experience in programming to learn and master the content within this book. This material, created by forensic professionals, was written with a unique perspective and understanding for examiners who wish to learn programming.

Design cost-efficient database solutions, scale enterprise operations and reduce overhead business costs with MySQL Key Features * Explore the new and advanced features of MySQL 8.0 * Use advanced techniques to optimize MySQL performance * Create MySQL-based applications for your enterprise with the help of practical examples Book Description Advanced MySQL 8 teaches you to enhance your existing database infrastructure and build various tools to improve your enterprise applications and overall website performance. The book starts with the new and exciting MySQL 8.0 features and how to utilize them for maximum efficiency. As you make your way through the chapters, you will learn to optimize MySQL performance using indexes and advanced data query techniques for large queries. You will also discover MySQL Server 8.0 settings and work with the MySQL data dictionary to boost the performance of your database. In the concluding chapters, you will cover MySQL 8.0 Group Replication, which will enable you to create elastic, highly available, and fault-tolerant replication topologies. You will also explore backup and recovery techniques for your databases and understand important tips and tricks to help your critical data reach its full potential. By the end of this book, you’ll have learned about new MySQL 8.0 security features that allow a database administrator (DBA) to simplify user management and increase the security of their multi-user environments. What you will learn * Explore new and exciting features of MySQL 8.0 * Analyze and optimize large MySQL queries * Understand MySQL Server 8.0 settings * Master the deployment of Group Replication and use it in an InnoDB cluster * Monitor large distributed databases * Discover different types of backups and recovery methods for your databases * Explore tips to help your critical data reach its full potential Who this book is for Advanced MySQL 8 is for database administrators, data architects, and database developers who want to dive deeper into building advanced database applications in the MySQL environment.

A comprehensive guide to building full stack applications covering frontend and server-side programming, data management, and web security Key Features * Unleash the power of React Hooks to build interactive and complex user interfaces * Build scalable full stack applications designed to meet demands of modern users * Understand how the Axios library simplifies CRUD operations Book Description React Hooks have changed the way React components are coded. They enable you to write components in a more intuitive way without using classes, which makes your code easier to read and maintain. Building on from the previous edition, this book is updated with React Hooks and the latest changes introduced in create-react-app and Spring Boot 2.1. This book starts with a brief introduction to Spring Boot. You’ll understand how to use dependency injection and work with the data access layer of Spring using Hibernate as the ORM tool. You’ll then learn how to build your own RESTful API endpoints for web applications. As you advance, the book introduces you to other Spring components, such as Spring Security to help you secure the backend. Moving on, you’ll explore React and its app development environment and components for building your frontend. Finally, you’ll create a Docker container for your application by implementing the best practices that underpin professional full stack web development. By the end of this book, you’ll be equipped with all the knowledge you need to build modern full stack applications with Spring Boot for the backend and React for the frontend. What you will learn * Create a RESTful web service with Spring Boot * Grasp the fundamentals of dependency injection and how to use it for backend development * Discover techniques for securing the backend using Spring Security * Understand how to use React for frontend programming * Benefit from the Heroku cloud server by deploying your application to it * Delve into the techniques for creating unit tests using JUnit * Explore the Material UI component library to make more user-friendly user interfaces Who this book is for If you are a Java developer familiar with Spring, but are new to building full stack applications, this is the book for you.

Understand the nitty-gritty of Cybersecurity with ease Key Features * Align your security knowledge with industry leading concepts and tools * Acquire required skills and certifications to survive the ever changing market needs * Learn from industry experts to analyse, implement, and maintain a robust environment Book Description It's not a secret that there is a huge talent gap in the cybersecurity industry. Everyone is talking about it including the prestigious Forbes Magazine, Tech Republic, CSO Online, DarkReading, and SC Magazine, among many others. Additionally, Fortune CEO's like Satya Nadella, McAfee's CEO Chris Young, Cisco's CIO Colin Seward along with organizations like ISSA, research firms like Gartner too shine light on it from time to time. This book put together all the possible information with regards to cybersecurity, why you should choose it, the need for cyber security and how can you be part of it and fill the cybersecurity talent gap bit by bit. Starting with the essential understanding of security and its needs, we will move to security domain changes and how artificial intelligence and machine learning are helping to secure systems. Later, this book will walk you through all the skills and tools that everyone who wants to work as security personal need to be aware of. Then, this book will teach readers how to think like an attacker and explore some advanced security methodologies. Lastly, this book will deep dive into how to build practice labs, explore real-world use cases and get acquainted with various cybersecurity certifications. By the end of this book, readers will be well-versed with the security domain and will be capable of making the right choices in the cybersecurity field. What you will learn * Get an overview of what cybersecurity is and learn about the various faces of cybersecurity as well as identify domain that suits you best * Plan your transition into cybersecurity in an efficient and effective way * Learn how to build upon your existing skills and experience in order to prepare for your career in cybersecurity Who this book is for This book is targeted to any IT professional who is looking to venture in to the world cyber attacks and threats. Anyone with some understanding or IT infrastructure workflow will benefit from this book. Cybersecurity experts interested in enhancing their skill set will also find this book useful.

Plan and build useful machine learning systems for financial services, with full working Python code Key Features * Build machine learning systems that will be useful across the financial services industry * Discover how machine learning can solve finance industry challenges * Gain the machine learning insights and skills fintech companies value most Book Description Machine learning skills are essential for anybody working in financial data analysis. Machine Learning for Finance shows you how to build machine learning models for use in financial services organizations. It shows you how to work with all the key machine learning models, from simple regression to advanced neural networks. You will see how to use machine learning to automate manual tasks, identify and address systemic bias, and find new insights and patterns hidden in available data. Machine Learning for Finance encourages and equips you to find new ways to use data to serve an organization’s business goals. Broad in scope yet deeply practical in approach, Machine Learning for Finance will help you to apply machine learning in all parts of a financial organization’s infrastructure. If you work or plan to work in fintech, and want to gain one of the most valuable skills in the sector today, this book is for you. What you will learn * Practical machine learning for the finance sector * Build machine learning systems that support the goals of financial organizations * Think creatively about problems and how machine learning can solve them * Identify and reduce sources of bias from machine learning models * Apply machine learning to structured data, natural language, photographs, and written text related to finance * Use machine learning to detect fraud, forecast financial trends, analyze customer sentiments, and more * Implement heuristic baselines, time series, generative models, and reinforcement learning in Python, scikit-learn, Keras, and TensorFlow Who this book is for Machine Learning for Finance is for financial professionals who want to develop and apply machine learning skills, and for students entering the field. You should be comfortable with Python and the basic data science stack, such as NumPy, pandas, and Matplotlib, to get the most out of this book.

This quick start guide will bring the readers to a basic level of understanding when it comes to the Machine Learning (ML) development lifecycle, will introduce Go ML libraries and then will exemplify common ML methods such as Classification, Regression, and Clustering Key Features * Your handy guide to building machine learning workflows in Go for real-world scenarios * Build predictive models using the popular supervised and unsupervised machine learning techniques * Learn all about deployment strategies and take your ML application from prototype to production ready Book Description Machine learning is an essential part of today's data-driven world and is extensively used across industries, including financial forecasting, robotics, and web technology. This book will teach you how to efficiently develop machine learning applications in Go. The book starts with an introduction to machine learning and its development process, explaining the types of problems that it aims to solve and the solutions it offers. It then covers setting up a frictionless Go development environment, including running Go interactively with Jupyter notebooks. Finally, common data processing techniques are introduced. The book then teaches the reader about supervised and unsupervised learning techniques through worked examples that include the implementation of evaluation metrics. These worked examples make use of the prominent open-source libraries GoML and Gonum. The book also teaches readers how to load a pre-trained model and use it to make predictions. It then moves on to the operational side of running machine learning applications: deployment, Continuous Integration, and helpful advice for effective logging and monitoring. At the end of the book, readers will learn how to set up a machine learning project for success, formulating realistic success criteria and accurately translating business requirements into technical ones. What you will learn * Understand the types of problem that machine learning solves, and the various approaches * Import, pre-process, and explore data with Go to make it ready for machine learning algorithms * Visualize data with gonum/plot and Gophernotes * Diagnose common machine learning problems, such as overfitting and underfitting * Implement supervised and unsupervised learning algorithms using Go libraries * Build a simple web service around a model and use it to make predictions Who this book is for This book is for developers and data scientists with at least beginner-level knowledge of Go, and a vague idea of what types of problem Machine Learning aims to tackle. No advanced knowledge of Go (and no theoretical understanding of the math that underpins Machine Learning) is required.

Build state-of-the-art web applications quickly and efficiently using Flask and related technologies with Python 3 Key Features * Updated to Flask 1.0.3 and Python 3.7 with coverage of Microservices * Get the most out of the powerful Flask framework and maintain the flexibility of your design choices * Write cleaner and maintainable code with the help of sample apps Book Description Flask, the lightweight Python web framework, is popular due to its powerful modular design that lets you build scalable web apps. With this recipe-based guide, you’ll explore modern solutions and best practices for Flask web development. Updated to the latest version of Flask and Python 3, this second edition of Flask Framework Cookbook moves away from some of the old and obsolete libraries and introduces recipes on bleeding edge technologies. You’ll discover different ways of using Flask to create, deploy, and manage microservices. This Flask Python book starts by covering the different configurations that a Flask application can make use of, and then helps you work with templates and learn about the ORM and view layers. You’ll also be able to write an admin interface and get to grips with debugging and logging errors. Finally, you’ll grasp a variety of deployment and post-deployment techniques for platforms such as Apache, Tornado, and Heroku. By the end of this book, you’ll have gained all the knowledge you need to write Flask applications in the best possible way and scale them using standard industry practices. What you will learn * Explore web application development in Flask, right from installation to post-deployment stages * Make use of advanced templating and data modeling techniques * Discover effective debugging, logging, and error handling techniques in Flask * Integrate Flask with different technologies such as Redis, Sentry, and MongoDB * Deploy and package Flask applications with Docker and Kubernetes * Design scalable microservice architecture using AWS LambdaContinuous integration and Continuous deployment Who this book is for If you are a web developer who wants to learn more about developing scalable and production-ready applications in Flask, this is the book for you. You’ll also find this book useful if you are already aware of Flask's major extensions and want to use them for better application development. Basic Python programming experience along with basic understanding of Flask is assumed.

Leverage the features of Azure SQL database and become an expert in data management Key Features * Explore ways to create shards and elastic pools to scale Azure SQL databases * Automate common management tasks with PowerShell * Implement over 40 practical activities and exercises to reinforce your learning Book Description Despite being the cloud version of SQL Server, Azure SQL Database differs in key ways when it comes to management, maintenance, and administration. This book shows you how to administer Azure SQL database to fully benefit from its wide range of features and functionality. Professional Azure SQL Database Administration begins by covering the architecture and explaining the difference between Azure SQL Database and the on-premise SQL Server to help you get comfortable with Azure SQL database. You’ll perform common tasks such as migrating, backing up, and restoring a SQL Server database to an Azure database. As you progress, you’ll study how you can save costs and manage and scale multiple SQL Databases using elastic pools. You’ll also implement a disaster recovery solution using standard and active geo-replication. Whether it is learning different techniques to monitor and tune an Azure SQL database or improving performance using in-memory technology, this book will enable you to make the most out of Azure SQL database features and functionality for data management solutions. By the end of this book, you’ll be well versed with key aspects of an Azure SQL database instance, such as migration, backup restorations, performance optimization, high availability, and disaster recovery. What you will learn * Understand Azure SQL Database configuration and pricing options * Provision a new SQL database or migrate an existing on-premise SQL Server database to Azure SQL Database * Back up and restore Azure SQL Database * Secure an Azure SQL database * Scale an Azure SQL database * Monitor and tune an Azure SQL database * Implement high availability and disaster recovery with Azure SQL Database * Automate common management tasks with PowerShell * Develop a scalable cloud solution with Azure SQL Database * Manage, maintain, and secure managed instances Who this book is for If you’re a database administrator, database developer, or an application developer interested in developing new applications or migrating existing ones with Azure SQL database, this book is for you. Prior experience of working with an on-premise SQL Server or Azure SQL database along with a basic understanding of PowerShell scripts and C# code is necessary to grasp the concepts covered in this book.

Master a range of machine learning domains with real-world projects using TensorFlow for R, H2O, MXNet, and more Key Features *Master machine learning, deep learning, and predictive modeling concepts in R 3.5 *Build intelligent end-to-end projects for finance, retail, social media, and a variety of domains *Implement smart cognitive models with helpful tips and best practices Book Description R is one of the most popular languages when it comes to performing computational statistics (statistical computing) easily and exploring the mathematical side of machine learning. With this book, you will leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization. This book will help you test your knowledge and skills, guiding you on how to build easily through to complex machine learning projects. You will first learn how to build powerful machine learning models with ensembles to predict employee attrition. Next, you’ll implement a joke recommendation engine and learn how to perform sentiment analysis on Amazon reviews. You’ll also explore different clustering techniques to segment customers using wholesale data. In addition to this, the book will get you acquainted with credit card fraud detection using autoencoders, and reinforcement learning to make predictions and win on a casino slot machine. By the end of the book, you will be equipped to confidently perform complex tasks to build research and commercial projects for automated operations. What you will learn *Explore deep neural networks and various frameworks that can be used in R *Develop a joke recommendation engine to recommend jokes that match users’ tastes *Create powerful ML models with ensembles to predict employee attrition *Build autoencoders for credit card fraud detection *Work with image recognition and convolutional neural networks *Make predictions for casino slot machine using reinforcement learning *Implement NLP techniques for sentiment analysis and customer segmentation Who this book is for If you’re a data analyst, data scientist, or machine learning developer who wants to master machine learning concepts using R by building real-world projects, this is the book for you. Each project will help you test your skills in implementing machine learning algorithms and techniques. A basic understanding of machine learning and working knowledge of R programming is necessary to get the most out of this book.

Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries Key Features *Build a strong foundation in neural networks and deep learning with Python libraries *Explore advanced deep learning techniques and their applications across computer vision and NLP *Learn how a computer can navigate in complex environments with reinforcement learning Book Description With the surge in artificial intelligence in applications catering to both business and consumer needs, deep learning is more important than ever for meeting current and future market demands. With this book, you’ll explore deep learning, and learn how to put machine learning to use in your projects. This second edition of Python Deep Learning will get you up to speed with deep learning, deep neural networks, and how to train them with high-performance algorithms and popular Python frameworks. You’ll uncover different neural network architectures, such as convolutional networks, recurrent neural networks, long short-term memory (LSTM) networks, and capsule networks. You’ll also learn how to solve problems in the fields of computer vision, natural language processing (NLP), and speech recognition. You'll study generative model approaches such as variational autoencoders and Generative Adversarial Networks (GANs) to generate images. As you delve into newly evolved areas of reinforcement learning, you’ll gain an understanding of state-of-the-art algorithms that are the main components behind popular games Go, Atari, and Dota. By the end of the book, you will be well-versed with the theory of deep learning along with its real-world applications. What you will learn *Grasp the mathematical theory behind neural networks and deep learning processes *Investigate and resolve computer vision challenges using convolutional networks and capsule networks *Solve generative tasks using variational autoencoders and Generative Adversarial Networks *Implement complex NLP tasks using recurrent networks (LSTM and GRU) and attention models *Explore reinforcement learning and understand how agents behave in a complex environment *Get up to date with applications of deep learning in autonomous vehicles Who this book is for This book is for data science practitioners, machine learning engineers, and those interested in deep learning who have a basic foundation in machine learning and some Python programming experience. A background in mathematics and conceptual understanding of calculus and statistics will help you gain maximum benefit from this book.

A practical guide that helps you progress to using modern integration methods and leverage new cloud capability models Key Features * Design critical hybrid integration solutions for your organization * Gain in-depth knowledge of how to build cloud-native integration solutions * Leverage cognitive services to build smart cloud solutions Book Description With more enterprises adapting cloud-based and API-based solutions, application integration has become more relevant and significant than ever before. Parallelly, Serverless Integration has gained popularity, as it helps agile organizations to build integration solutions quickly without having to worry about infrastructure costs. With Microsoft Azure’s serverless offerings, such as Logic Apps, Azure Functions, API Management, Azure Event Grid and Service Bus, organizations can build powerful, secure, and scalable integration solutions with ease. The primary objective of this book is to help you to understand various serverless offerings included within Azure Integration Services, taking you through the basics and industry practices and patterns. This book starts by explaining the concepts of services such as Azure Functions, Logic Apps, and Service Bus with hands-on examples and use cases. After getting to grips with the basics, you will be introduced to API Management and building B2B solutions using Logic Apps Enterprise Integration Pack. This book will help readers to understand building hybrid integration solutions and touches upon Microsoft Cognitive Services and leveraging them in modern integration solutions. Industry practices and patterns are brought to light at appropriate opportunities while explaining various concepts. What you will learn * Learn about the design principles of Microsoft Azure Serverless Integration * Get insights into Azure Functions, Logic Apps, Azure Event Grid and Service Bus * Secure and manage your integration endpoints using Azure API Management * Build advanced B2B solutions using Logic Apps, Enterprise Integration Pack * Monitor integration solutions using tools available on the market * Discover design patterns for hybrid integration Who this book is for Serverless Integration Design Patterns with Azure is for you if you are a solution architect or integration professional aiming to build complex cloud solutions for your organization. Developers looking to build next-level hybrid or cloud solutions will also find this book useful. Prior programming knowledge is necessary.

Designing and deploying solutions using the SAP BusinessObjects Business Intelligence platform 4.2. Key Features * Get up and running with the SAP BusinessObjects Business Intelligence platform * Perform effective data analysis and visualization for actionable insights * Enhance your BI strategy by creating different types of reports and dashboards using SAP BusinessObjects Book Description The SAP BusinessObjects Business Intelligence platform is a powerful reporting and analysis tool. This book is the ideal introduction to the SAP BusinessObjects Business Intelligence platform, introducing you to its data visualization, visual analytics, reporting, and dashboarding capabilities. The book starts with an overview of the BI platform and various data sources for reporting. Then, we move on to looking at data visualization, analysis, reporting, and analytics using BusinessObjects Business Intelligence tools. You will learn about the features associated with reporting, scheduling, and distribution and learn how to deploy the platform. Toward the end, you will learn about the strategies and factors that should be considered during deployment. By the end, you will be confident working with the SAP BusinessObjects Business Intelligence platform to deliver better insights for more effective decision making. What you will learn * Work with various tools to create interactive data visualization and analysis * Query, report, and analyze with SAP Business Objects Web Intelligence * Create a report in SAP Crystal Reports for Enterprise * Visualize and manipulate data using an SAP Lumira Storyboard * Deep dive into the workings of the SAP predictive analytics tool * Deploy and configure SAP BO Intelligence platform 4.2 Who this book is for This book is for Business Intelligence professionals and existing SAP ecosystem users who want to perform effective Business Intelligence using SAP BusinessObjects.