Build modular React web apps that are scalable, maintainable and powerful using design patterns and insightful practices Key Features * Get familiar with design patterns in React like Render props and Controlled/uncontrolled inputs * Learn about class/ functional, style and high order components with React * Work through examples that can be used to create reusable code and extensible designs Book Description React is an adaptable JavaScript library for building complex UIs from small, detached bits called components. This book is designed to take you through the most valuable design patterns in React, helping you learn how to apply design patterns and best practices in real-life situations. You’ll get started by understanding the internals of React, in addition to covering Babel 7 and Create React App 2.0, which will help you write clean and maintainable code. To build on your skills, you will focus on concepts such as class components, stateless components, and pure components. You'll learn about new React features, such as the context API and React Hooks that will enable you to build components, which will be reusable across your applications. The book will then provide insights into the techniques of styling React components and optimizing them to make applications faster and more responsive. In the concluding chapters, you’ll discover ways to write tests more effectively and learn how to contribute to React and its ecosystem. By the end of this book, you will be equipped with the skills you need to tackle any developmental setbacks when working with React. You’ll be able to make your applications more flexible, efficient, and easy to maintain, thereby giving your workflow a boost when it comes to speed, without reducing quality. What you will learn * Get familiar with the new React features,like context API and React Hooks * Learn the techniques of styling and optimizing React components * Make components communicate with each other by applying consolidate patterns * Use server-side rendering to make applications load faster * Write a comprehensive set of tests to create robust and maintainable code * Build high-performing applications by optimizing components Who this book is for This book is for web developers who want to increase their understanding of React and apply it to real-life application development. Prior experience with React and JavaScript is assumed.

Explore the different data mining techniques using the libraries and packages offered by Python Key Features * Grasp the basics of data loading, cleaning, analysis, and visualization * Use the popular Python libraries such as NumPy, pandas, matplotlib, and scikit-learn for data mining * Your one-stop guide to build efficient data mining pipelines without going into too much theory Book Description Data mining is a necessary and predictable response to the dawn of the information age. It is typically defined as the pattern and/ or trend discovery phase in the data mining pipeline, and Python is a popular tool for performing these tasks as it offers a wide variety of tools for data mining. This book will serve as a quick introduction to the concept of data mining and putting it to practical use with the help of popular Python packages and libraries. You will get a hands-on demonstration of working with different real-world datasets and extracting useful insights from them using popular Python libraries such as NumPy, pandas, scikit-learn, and matplotlib. You will then learn the different stages of data mining such as data loading, cleaning, analysis, and visualization. You will also get a full conceptual description of popular data transformation, clustering, and classification techniques. By the end of this book, you will be able to build an efficient data mining pipeline using Python without any hassle. What you will learn * Explore the methods for summarizing datasets and visualizing/plotting data * Collect and format data for analytical work * Assign data points into groups and visualize clustering patterns * Learn how to predict continuous and categorical outputs for data * Clean, filter noise from, and reduce the dimensions of data * Serialize a data processing model using scikit-learn’s pipeline feature * Deploy the data processing model using Python’s pickle module Who this book is for Python developers interested in getting started with data mining will love this book. Budding data scientists and data analysts looking to quickly get to grips with practical data mining with Python will also find this book to be useful. Knowledge of Python programming is all you need to get started.

Build, design and improve advanced business intelligence solutions using Tableau’s latest features, including Tableau Prep, Tableau Hyper, and Tableau Server Key Features * Master new features in Tableau 2019.1 to solve real-world analytics challenges * Perform Geo-Spatial Analytics, Time Series Analysis, and self-service analytics using real-life examples * Build and publish dashboards and explore storytelling using Python and MATLAB integration support Book Description Tableau is one of the leading business intelligence (BI) tools used to solve BI and analytics challenges. With this book, you will master Tableau's features and offerings in various paradigms of the BI domain. This book is also the second edition of the popular Mastering Tableau series, with new features, examples, and updated code. The book covers essential Tableau concepts and its advanced functionalities. Using Tableau Hyper and Tableau Prep, you’ll be able to handle and prepare data easily. You’ll gear up to perform complex joins, spatial joins, union, and data blending tasks using practical examples. Following this, you’ll learn how to perform data densification to make displaying granular data easier. Next, you’ll explore expert-level examples to help you with advanced calculations, mapping, and visual design using various Tableau extensions. With the help of examples, you’ll also learn about improving dashboard performance, connecting Tableau Server, and understanding data visualizations. In the final chapters, you’ll cover advanced use cases such as Self-Service Analytics, Time Series Analytics, and Geo-Spatial Analytics, and learn to connect Tableau to R, Python, and MATLAB. By the end of this book, you’ll have mastered the advanced offerings of Tableau and be able to tackle common and not-so-common challenges faced in the BI domain. What you will learn * Get up to speed with various Tableau components * Master data preparation techniques using Tableau Prep * Discover how to use Tableau to create a PowerPoint-like presentation * Understand different Tableau visualization techniques and dashboard designs * Interact with the Tableau server to understand its architecture and functionalities * Study advanced visualizations and dashboard creation techniques * Brush up on powerful Self-Service Analytics, Time Series Analytics, and Geo-Spatial Analytics Who this book is for This book is designed for business analysts, BI professionals and data analysts who want to master Tableau to solve a range of data science and business intelligence problems. The book is ideal if you have a good understanding of Tableau and want to take your skills to the next level.

Design interactive graphics and visuals for your data-driven applications using the popular open-source Chart.js data visualization library. Key Features * Harness the power of JavaScript, HTML, and CSS to create interactive visualizations * Display quantitative information efficiently in the form of attractive charts by using Chart.js * A practical guide for creating data-driven applications using open-source JavaScript library Book Description Chart.js is a free, open-source data visualization library, maintained by an active community of developers in GitHub, where it rates as the second most popular data visualization library. If you want to quickly create responsive Web-based data visualizations for the Web, Chart.js is a great choice. This book guides the reader through dozens of practical examples, complete with code you can run and modify as you wish. It is a practical hands-on introduction to Chart.js. If you have basic knowledge of HTML, CSS and JavaScript you can learn to create beautiful interactive Web Canvas-based visualizations for your data using Chart.js. This book will help you set up Chart.js in a Web page and show how to create each one of the eight Chart.js chart types. You will also learn how to configure most properties that override Chart’s default styles and behaviors. Practical applications of Chart.js are exemplified using real data files obtained from public data portals. You will learn how to load, parse, filter and select the data you wish to display from those files. You will also learn how to create visualizations that reveal patterns in the data. This book is based on Chart.js version 2.7.3 and ES2015 JavaScript. By the end of the book, you will be able to create beautiful, efficient and interactive data visualizations for the Web using Chart.js. What you will learn * Learn how to create interactive and responsive data visualizations using Chart.js * Learn how to create Canvas-based graphics without Canvas programming * Create composite charts and configure animated data updates and transitions * Efficiently display quantitative information using bar and line charts, scatterplots, and pie charts * Learn how to load, parse, and filter external files in JSON and CSV formats * Understand the benefits of using a data visualization framework Who this book is for The ideal target audience of this book includes web developers and designers, data journalists, data scientists and artists who wish to create interactive data visualizations for the Web. Basic knowledge of HTML, CSS, and JavaScript is required. No Canvas knowledge is necessary.

Discover advanced virtualization techniques and strategies to deliver centralized desktop and application services Key Features * Leverage advanced desktop virtualization techniques and strategies to transform your organization * Build better virtualized services for your users with VMware Horizon 7.8 * Develop and deploy end-to-end virtualized solutions Book Description Desktop virtualization can be tough, but VMware Horizon 7.8 changes all that. With a rich and adaptive UX, improved security,and a range of useful features for storage and networking optimization, there's plenty to love. But to properly fall in love with it, you need to know how to use it, and that means venturing deeper into the software and taking advantage of its extensive range of features, many of which are underused and underpromoted. This guide will take you through everything you need to know to not only successfully virtualize your desktop infrastructure, but also to maintain and optimize it to keep all your users happy. We'll show you how to assess and analyze your infrastructure, and how to use that analysis to design a solution that meets your organizational and user needs. Once you've done that, you'll find out how to build your virtualized environment, before deploying your virtualized solution. But more than that,we'll also make sure you know everything you need to know about the full range of features on offer, including the mobile cloud, so that you can use them to take full control of your virtualized infrastructure. What you will learn * Successfully configure Horizon 7.8 for the needs of your users * Deliver virtual desktops, session-based desktops, and hosted applications * Become familiar with how to develop, and deploy, a complete, end-to-end solution * Discover how to optimize desktop OS images for virtual desktops * Build, optimize, and tune desktop operating systems to deliver a superior end user experience * Explore the Horizon 7.8 infrastructure so that you can take full advantage of it Who this book is for This book is ideal for system admins, and solution architects interested in gaining hands-on experience with virtualization. It will take you to an advanced level, but at a pace that ensures you are always solving real-world problems. Some experience in desktop management using Windows and Microsoft Office (and familiarity with Active Directory, SQL, Windows Remote Desktop Session Hosting, and VMware vSphere technology) is necessary.

A comprehensive guide to understanding network architecture, communication protocols, and network analysis to build secure applications compatible with the latest versions of C# 8 and .NET Core 3.0 Key Features * Explore various network architectures that make distributed programming possible * Learn how to make reliable software by writing secure interactions between clients and servers * Use .NET Core for network device automation, DevOps, and software-defined networking Book Description The C# language and the .NET Core application framework provide the tools and patterns required to make the discipline of network programming as intuitive and enjoyable as any other aspect of C# programming. With the help of this book, you will discover how the C# language and the .NET Core framework make this possible. The book begins by introducing the core concepts of network programming, and what distinguishes this field of programming from other disciplines. After this, you will gain insights into concepts such as transport protocols, sockets and ports, and remote data streams, which will provide you with a holistic understanding of how network software fits into larger distributed systems. The book will also explore the intricacies of how network software is implemented in a more explicit context, by covering sockets, connection strategies such as Transmission Control Protocol (TCP) and User Datagram Protocol (UDP), asynchronous processing, and threads. You will then be able to work through code examples for TCP servers, web APIs served over HTTP, and a Secure Shell (SSH) client. By the end of this book, you will have a good understanding of the Open Systems Interconnection (OSI) network stack, the various communication protocols for that stack, and the skills that are essential to implement those protocols using the C# programming language and the .NET Core framework. What you will learn * Understand the breadth of C#'s network programming utility classes * Utilize network-layer architecture and organizational strategies * Implement various communication and transport protocols within C# * Discover hands-on examples of distributed application development * Gain hands-on experience with asynchronous socket programming and streams * Learn how C# and the .NET Core runtime interact with a hosting network * Understand a full suite of network programming tools and features Who this book is for If you're a .NET developer or a system administrator with .NET experience and are looking to get started with network programming, then this book is for you. Basic knowledge of C# and .NET is assumed, in addition to a basic understanding of common web protocols and some high-level distributed system designs.

Efficiently deploy and manage Kubernetes clusters on a cloud Key Features * Deploy highly scalable applications with Kubernetes on Azure * Leverage AKS to deploy, manage, and operations of Kubernetes * Gain best practices from this guide to increase efficiency of container orchestration service on Cloud Book Description Microsoft is now one of the most significant contributors to Kubernetes open source projects. Kubernetes helps to create, configure, and manage a cluster of virtual machines that are preconfigured to run containerized applications. This book will be your resource for achieving successful container orchestration and deployment of Kubernetes clusters on Azure. You will learn how to deploy and manage highly scalable applications, along with how to set up a production-ready Kubernetes cluster on Azure. With this book, you will be able to reduce the complexity and operational overheads of managing a Kubernetes cluster on Azure. By the end of this book, you will not only be capable of deploying and managing Kubernetes clusters on Azure with ease, but also have the knowledge of industry best practices to work with advanced Azure Kubernetes Services (AKS) concepts for complex systems. What you will learn * Get to grips with Microsoft AKS deployment, management, and operations * Learn about the benefits of using Microsoft AKS, as well as the limitations, and avoid potential problems * Integrate Microsoft toolchains such as Visual Studio Code, and Git * Implement simple and advanced AKS solutions * Implement the automated scalability and high reliability of secure deployments with Microsoft AKS * Use kubectl commands to monitor applications Who this book is for If you’re a cloud engineer, cloud solution provider, sysadmin, site reliability engineer, or a developer interested in DevOps and are looking for an extensive guide to running Kubernetes in the Azure environment then, this book is for you. Though any previous knowledge of Kubernetes is not expected, some experience with Linux and Docker containers would be beneficial.

Gain a complete overview of Oracle CX Cloud Suite and its tools for functions ranging from marketing to sales and commerce to service Key Features * Make optimal use of your Oracle CX Cloud Suite to improve business results * Achieve improved customer insights through Oracle CX’s advanced capabilities * Learn how to design a CX solution architecture Book Description Oracle CX Cloud offers features and capabilities that help companies excel at sales, customer management, and much more. This book is a detailed guide to implementing cloud solutions and helping administrators of all levels thoroughly understand the platform. Oracle CX Cloud Suite begins with an introduction to high-level Oracle architecture and examines what CX offers over CRM. You’ll explore the different cloud-based tools for marketing, sales, and customer services, among others. The book then delves into deployment by covering basic settings, setting up users, and provisioning. You’ll see how to integrate the CX suite to work together to interact with the environment and connect with legacy systems, social connectors, and internet services. The book concludes with a use case demonstrating how the entire Oracle CX Suite is set up, and also covers how to leverage Oracle ICS and Oracle CX Cloud for hybrid deployment. By end of the book, you will have learned about the working of the Oracle CX Cloud Suite and how to orchestrate user experience across all products seamlessly. What you will learn * Differentiate between Oracle CRM and CX Cloud suites * Explore a variety of Oracle CX Cloud tools for marketing and sales * Set up users and database connections during deployment * Employ Cloud Suite CX tools to aid in planning and analysis * Implement hybrid Oracle CX solutions and connect with legacy systems * Integrate with social media connectors like Facebook and LinkedIn * Leverage Oracle ICS and Oracle CX Suite to improve business results Who this book is for This book is for administrators who want to develop and strengthen their Oracle CX Cloud Suite skills in the areas of configuration and system management. Whether you are a new administrator or an experienced professional, this book will enhance your understanding of the new Oracle CX features.

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

Conquer complex and interesting programming challenges by building robust and concurrent applications with caches, cryptography, and parallel programming. Key Features * Understand how to use .NET frameworks like the Task Parallel Library (TPL)and CryptoAPI * Develop a containerized application based on microservices architecture * Gain insights into memory management techniques in .NET Core Book Description This Learning Path shows you how to create high performing applications and solve programming challenges using a wide range of C# features. You’ll begin by learning how to identify the bottlenecks in writing programs, highlight common performance pitfalls, and apply strategies to detect and resolve these issues early. You'll also study the importance of micro-services architecture for building fast applications and implementing resiliency and security in .NET Core. Then, you'll study the importance of defining and testing boundaries, abstracting away third-party code, and working with different types of test double, such as spies, mocks, and fakes. In addition to describing programming trade-offs, this Learning Path will also help you build a useful toolkit of techniques, including value caching, statistical analysis, and geometric algorithms. This Learning Path includes content from the following Packt products: * C# 7 and .NET Core 2.0 High Performance by Ovais Mehboob Ahmed Khan * Practical Test-Driven Development using C# 7 by John Callaway, Clayton Hunt * The Modern C# Challenge by Rod Stephens What you will learn * Measure application performance using BenchmarkDotNet * Leverage the Task Parallel Library (TPL) and Parallel Language Integrated Query (PLINQ)library to perform asynchronous operations * Modify a legacy application to make it testable * Use LINQ and PLINQ to search directories for files matching patterns * Find areas of polygons using geometric operations * Randomize arrays and lists with extension methods * Use cryptographic techniques to encrypt and decrypt strings and files Who this book is for If you want to improve the speed of your code and optimize the performance of your applications, or are simply looking for a practical resource on test driven development, this is the ideal Learning Path for you. Some familiarity with C# and .NET will be beneficial.

Create distributed applications with clever design patterns to solve complex problems Key Features * Set up and run distributed algorithms on a cluster using Dask and PySpark * Master skills to accurately implement concurrency in your code * Gain practical experience of Python design patterns with real-world examples Book Description This Learning Path shows you how to leverage the power of both native and third-party Python libraries for building robust and responsive applications. You will learn about profilers and reactive programming, concurrency and parallelism, as well as tools for making your apps quick and efficient. You will discover how to write code for parallel architectures using TensorFlow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. With the knowledge of how Python design patterns work, you will be able to clone objects, secure interfaces, dynamically choose algorithms, and accomplish much more in high performance computing. By the end of this Learning Path, you will have the skills and confidence to build engaging models that quickly offer efficient solutions to your problems. This Learning Path includes content from the following Packt products: * Python High Performance - Second Edition by Gabriele Lanaro * Mastering Concurrency in Python by Quan Nguyen * Mastering Python Design Patterns by Sakis Kasampalis What you will learn * Use NumPy and pandas to import and manipulate datasets * Achieve native performance with Cython and Numba * Write asynchronous code using asyncio and RxPy * Design highly scalable programs with application scaffolding * Explore abstract methods to maintain data consistency * Clone objects using the prototype pattern * Use the adapter pattern to make incompatible interfaces compatible * Employ the strategy pattern to dynamically choose an algorithm Who this book is for This Learning Path is specially designed for Python developers who want to build high-performance applications and learn about single core and multi-core programming, distributed concurrency, and Python design patterns. Some experience with Python programming language will help you get the most out of this Learning Path.

Integrate Redux with React and other front-end JavaScript frameworks efficiently and manage application states effectively Key Features * Get better at building web applications with state management using Redux * Learn the fundamentals of Redux to structure your app more efficiently * This guide will teach you develop complex apps that would be easier to maintain Book Description Starting with a detailed overview of Redux, we will follow the test-driven development (TDD) approach to develop single-page applications. We will set up JEST for testing and use JEST to test React, Redux, Redux-Sage, Reducers, and other components. We will then add important middleware and set up immutableJS in our application. We will use common data structures such as Map, List, Set, and OrderedList from the immutableJS framework. We will then add user interfaces using ReactJS, Redux-Form, and Ant Design. We will explore the use of react-router-dom and its functions. We will create a list of routes that we will need in order to create our application, and explore routing on the server site and create the required routes for our application. We will then debug our application and integrate Redux Dev tools. We will then set up our API server and create the API required for our application. We will dive into a modern approach to structuring our server site components in terms of Model, Controller, Helper functions, and utilities functions. We will explore the use of NodeJS with Express to build the REST API components. Finally, we will venture into the possibilities of extending the application for further research, including deployment and optimization. What you will learn * Follow the test-driven development (TDD) approach to develop a single-page application * Add important middleware, such as Redux store middleware, redux-saga middleware, and language middleware, to your application * Understand how to use immutableJS in your application * Build interactive components using ReactJS * Configure react-router-redux and explore the differences between react-router-dom and react-router-redux * Use Redux Dev tools to debug your application * Set up our API server and create the API required for our application Who this book is for This book is meant for JavaScript developers interesting in learning state management and building easy to maintain web applications.

Gain hands-on experience with industry-standard data analysis and machine learning tools in Python Key Features * Learn techniques to use data to identify the exact problem to be solved * Visualize data using different graphs * Identify how to select an appropriate algorithm for data extraction Book Description Data Science Projects with Python is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The book will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive. You will continue to build on your knowledge as you learn how to prepare data and feed it to machine learning algorithms, such as regularized logistic regression and random forest, using the scikit-learn package. You’ll discover how to tune the algorithms to provide the best predictions on new and, unseen data. As you delve into later chapters, you’ll be able to understand the working and output of these algorithms and gain insight into not only the predictive capabilities of the models but also their reasons for making these predictions. By the end of this book, you will have the skills you need to confidently use various machine learning algorithms to perform detailed data analysis and extract meaningful insights from unstructured data. What you will learn * Install the required packages to set up a data science coding environment * Load data into a Jupyter Notebook running Python * Use Matplotlib to create data visualizations * Fit a model using scikit-learn * Use lasso and ridge regression to reduce overfitting * Fit and tune a random forest model and compare performance with logistic regression * Create visuals using the output of the Jupyter Notebook Who this book is for If you are a data analyst, data scientist, or a business analyst who wants to get started with using Python and machine learning techniques to analyze data and predict outcomes, this book is for you. Basic knowledge of computer programming and data analytics is a must. Familiarity with mathematical concepts such as algebra and basic statistics will be useful.

Concepts, tools, and techniques to explore deep learning architectures and methodologies Key Features * Explore advanced deep learning architectures using various datasets and frameworks * Implement deep architectures for neural network models such as CNN, RNN, GAN, and many more * Discover design patterns and different challenges for various deep learning architectures Book Description Deep learning architectures are composed of multilevel nonlinear operations that represent high-level abstractions; this allows you to learn useful feature representations from the data. This book will help you learn and implement deep learning architectures to resolve various deep learning research problems. Hands-On Deep Learning Architectures with Python explains the essential learning algorithms used for deep and shallow architectures. Packed with practical implementations and ideas to help you build efficient artificial intelligence systems (AI), this book will help you learn how neural networks play a major role in building deep architectures. You will understand various deep learning architectures (such as AlexNet, VGG Net, GoogleNet) with easy-to-follow code and diagrams. In addition to this, the book will also guide you in building and training various deep architectures such as the Boltzmann mechanism, autoencoders, convolutional neural networks (CNNs), recurrent neural networks (RNNs), natural language processing (NLP), GAN, and more—all with practical implementations. By the end of this book, you will be able to construct deep models using popular frameworks and datasets with the required design patterns for each architecture. You will be ready to explore the potential of deep architectures in today's world. What you will learn * Implement CNNs, RNNs, and other commonly used architectures with Python * Explore architectures such as VGGNet, AlexNet, and GoogLeNet * Build deep learning architectures for AI applications such as face and image recognition, fraud detection, and many more * Understand the architectures and applications of Boltzmann machines and autoencoders with concrete examples * Master artificial intelligence and neural network concepts and apply them to your architecture * Understand deep learning architectures for mobile and embedded systems Who this book is for If you’re a data scientist, machine learning developer/engineer, or deep learning practitioner, or are curious about AI and want to upgrade your knowledge of various deep learning architectures, this book will appeal to you. You are expected to have some knowledge of statistics and machine learning algorithms to get the best out of this book

Start empowering users and protecting corporate data, while managing identities and access with Microsoft Azure in different environments Key Features * Understand how to identify and manage business drivers during transitions * Explore Microsoft Identity and Access Management as a Service (IDaaS) solution * Over 40 playbooks to support your learning process with practical guidelines Book Description Microsoft Azure and its Identity and access management are at the heart of Microsoft's software as service products, including Office 365, Dynamics CRM, and Enterprise Mobility Management. It is crucial to master Microsoft Azure in order to be able to work with the Microsoft Cloud effectively. You’ll begin by identifying the benefits of Microsoft Azure in the field of identity and access management. Working through the functionality of identity and access management as a service, you will get a full overview of the Microsoft strategy. Understanding identity synchronization will help you to provide a well-managed identity. Project scenarios and examples will enable you to understand, troubleshoot, and develop on essential authentication protocols and publishing scenarios. Finally, you will acquire a thorough understanding of Microsoft Information protection technologies. What you will learn * Apply technical descriptions to your business needs and deployments * Manage cloud-only, simple, and complex hybrid environments * Apply correct and efficient monitoring and identity protection strategies * Design and deploy custom Identity and access management solutions * Build a complete identity and access management life cycle * Understand authentication and application publishing mechanisms * Use and understand the most crucial identity synchronization scenarios * Implement a suitable information protection strategy Who this book is for This book is a perfect companion for developers, cyber security specialists, system and security engineers, IT consultants/architects, and system administrators who are looking for perfectly up–to-date hybrid and cloud-only scenarios. You should have some understanding of security solutions, Active Directory, access privileges/rights, and authentication methods. Programming knowledge is not required but can be helpful for using PowerShell or working with APIs to customize your solutions.

Harness the power of Python objects and data structures to implement algorithms for analyzing your data and efficiently extracting information Key Features * Turn your designs into working software by learning the Python syntax * Write robust code with a solid understanding of Python data structures * Understand when to use the functional or the OOP approach Book Description This Learning Path helps you get comfortable with the world of Python. It starts with a thorough and practical introduction to Python. You’ll quickly start writing programs, building websites, and working with data by harnessing Python's renowned data science libraries. With the power of linked lists, binary searches, and sorting algorithms, you'll easily create complex data structures, such as graphs, stacks, and queues. After understanding cooperative inheritance, you'll expertly raise, handle, and manipulate exceptions. You will effortlessly integrate the object-oriented and not-so-object-oriented aspects of Python, and create maintainable applications using higher level design patterns. Once you’ve covered core topics, you’ll understand the joy of unit testing and just how easy it is to create unit tests. By the end of this Learning Path, you will have built components that are easy to understand, debug, and can be used across different applications. This Learning Path includes content from the following Packt products: * Learn Python Programming - Second Edition by Fabrizio Romano * Python Data Structures and Algorithms by Benjamin Baka * Python 3 Object-Oriented Programming by Dusty Phillips What you will learn * Use data structures and control flow to write code * Use functions to bundle together a sequence of instructions * Implement objects in Python by creating classes and defining methods * Design public interfaces using abstraction, encapsulation and information hiding * Raise, define, and manipulate exceptions using special error objects * Create bulletproof and reliable software by writing unit tests * Learn the common programming patterns and algorithms used in Python Who this book is for If you are relatively new to coding and want to write scripts or programs to accomplish tasks using Python, or if you are an object-oriented programmer for other languages and seeking a leg up in the world of Python, then this Learning Path is for you. Though not essential, it will help you to have basic knowledge of programming and OOP.

Implement neural network architectures by building them from scratch for multiple real-world applications. Key Features * From scratch, build multiple neural network architectures such as CNN, RNN, LSTM in Keras * Discover tips and tricks for designing a robust neural network to solve real-world problems * Graduate from understanding the working details of neural networks and master the art of fine-tuning them Book Description This book will take you from the basics of neural networks to advanced implementations of architectures using a recipe-based approach. We will learn about how neural networks work and the impact of various hyper parameters on a network's accuracy along with leveraging neural networks for structured and unstructured data. Later, we will learn how to classify and detect objects in images. We will also learn to use transfer learning for multiple applications, including a self-driving car using Convolutional Neural Networks. We will generate images while leveraging GANs and also by performing image encoding. Additionally, we will perform text analysis using word vector based techniques. Later, we will use Recurrent Neural Networks and LSTM to implement chatbot and Machine Translation systems. Finally, you will learn about transcribing images, audio, and generating captions and also use Deep Q-learning to build an agent that plays Space Invaders game. By the end of this book, you will have developed the skills to choose and customize multiple neural network architectures for various deep learning problems you might encounter. What you will learn * Build multiple advanced neural network architectures from scratch * Explore transfer learning to perform object detection and classification * Build self-driving car applications using instance and semantic segmentation * Understand data encoding for image, text and recommender systems * Implement text analysis using sequence-to-sequence learning * Leverage a combination of CNN and RNN to perform end-to-end learning * Build agents to play games using deep Q-learning Who this book is for This intermediate-level book targets beginners and intermediate-level machine learning practitioners and data scientists who have just started their journey with neural networks. This book is for those who are looking for resources to help them navigate through the various neural network architectures; you'll build multiple architectures, with concomitant case studies ordered by the complexity of the problem. A basic understanding of Python programming and a familiarity with basic machine learning are all you need to get started with this book.

Learn to create and customize impressive Drupal 8 modules to extend your website's functionalities Key Features * Explore a plethora of Drupal 8 APIs and get the best out of them using the power of PHP coding * Learn to implement efficient data management and data security by creating dedicated modules for it. * Stay up to date with the changes introduced in the new Drupal 8 releases Book Description Drupal 8 comes with a release cycle that allows for new functionality to be added at a much faster pace. However, this also means code deprecations and changing architecture that you need to stay on top of. This book updates the first edition and includes the new functionality introduced in versions up to, and including 8.7. The book will first introduce you to the Drupal 8 architecture and its subsystems before diving into creating your first module with basic functionality. You will work with the Drupal logging and mailing systems, learn how to output data using the theme layer and work with menus and links programmatically. Then, you will learn how to work with different kinds of data storages, create custom entities, field types and leverage the Database API for lower level database queries. You will further see how to introduce JavaScript into your module, work with the various file systems and ensure the code you write works on multilingual sites. Finally, you will learn how to programmatically work with Views, write automated tests for your functionality and also write secure code in general. By the end, you will have learned how to develop your own custom module that can provide complex business solutions. And who knows, maybe you’ll even contribute it back to the Drupal community. What you will learn * Develop Drupal 8 modules that do all the things you want * Master numerous Drupal 8 sub-systems and APIs in the process * Model, store, manipulate and process data to serve your purposes * Display data and content in a clean and secure way using the Drupal 8 theme system * Test your business logic to prevent regressions * Stay ahead of the curve and write code following the current best practices Who this book is for The primary target of this book is Drupal developers who want to learn how to write modules and develop in Drupal 8. It is also intended for Drupal site builders and PHP developers who have basic Object Oriented Programming skills. A little bit of Symfony experience is helpful but not mandatory.

Use PySpark to easily crush messy data at-scale and discover proven techniques to create testable, immutable, and easily parallelizable Spark jobs Key Features * Work with large amounts of agile data using distributed datasets and in-memory caching * Source data from all popular data hosting platforms, such as HDFS, Hive, JSON, and S3 * Employ the easy-to-use PySpark API to deploy big data Analytics for production Book Description Apache Spark is an open source parallel-processing framework that has been around for quite some time now. One of the many uses of Apache Spark is for data analytics applications across clustered computers. In this book, you will not only learn how to use Spark and the Python API to create high-performance analytics with big data, but also discover techniques for testing, immunizing, and parallelizing Spark jobs. You will learn how to source data from all popular data hosting platforms, including HDFS, Hive, JSON, and S3, and deal with large datasets with PySpark to gain practical big data experience. This book will help you work on prototypes on local machines and subsequently go on to handle messy data in production and at scale. This book covers installing and setting up PySpark, RDD operations, big data cleaning and wrangling, and aggregating and summarizing data into useful reports. You will also learn how to implement some practical and proven techniques to improve certain aspects of programming and administration in Apache Spark. By the end of the book, you will be able to build big data analytical solutions using the various PySpark offerings and also optimize them effectively. What you will learn * Get practical big data experience while working on messy datasets * Analyze patterns with Spark SQL to improve your business intelligence * Use PySpark's interactive shell to speed up development time * Create highly concurrent Spark programs by leveraging immutability * Discover ways to avoid the most expensive operation in the Spark API: the shuffle operation * Re-design your jobs to use reduceByKey instead of groupBy * Create robust processing pipelines by testing Apache Spark jobs Who this book is for This book is for developers, data scientists, business analysts, or anyone who needs to reliably analyze large amounts of large-scale, real-world data. Whether you're tasked with creating your company's business intelligence function or creating great data platforms for your machine learning models, or are looking to use code to magnify the impact of your business, this book is for you.

Get to grips with pandas—a versatile and high-performance Python library for data manipulation, analysis, and discovery Key Features * Perform efficient data analysis and manipulation tasks using pandas * Apply pandas to different real-world domains using step-by-step demonstrations * Get accustomed to using pandas as an effective data exploration tool Book Description Data analysis has become a necessary skill in a variety of positions where knowing how to work with data and extract insights can generate significant value. Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification, using scikit-learn, to make predictions based on past data. By the end of this book, you will be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. What you will learn * Understand how data analysts and scientists gather and analyze data * Perform data analysis and data wrangling in Python * Combine, group, and aggregate data from multiple sources * Create data visualizations with pandas, matplotlib, and seaborn * Apply machine learning (ML) algorithms to identify patterns and make predictions * Use Python data science libraries to analyze real-world datasets * Use pandas to solve common data representation and analysis problems * Build Python scripts, modules, and packages for reusable analysis code Who this book is for This book is for data analysts, data science beginners, and Python developers who want to explore each stage of data analysis and scientific computing using a wide range of datasets. You will also find this book useful if you are a data scientist who is looking to implement pandas in machine learning. Working knowledge of Python programming language will be beneficial.

Gain useful insights to help you efficiently build, test, and migrate customized solutions on Business Central cloud and on-premise platforms Key Features * Explore enhanced functionalities and development best practices in Business Central * Develop powerful Business Central projects using the AL language * Master the new Business Central with easy-to-follow recipes Book Description Microsoft Dynamics 365 Business Central is a complete business management solution that can help you streamline business processes, connect individual departments in your company, and enhance customer interactions. Ok. That first part was really professional sounding, right? Now, let’s get into what this cookbook is going to do for you: put simply, it’s going to help you get things done. This book will help you get to grips with the latest development features and tools for building applications using Business Central. You’ll find recipes that will guide you in developing and testing applications that can be deployed to the cloud or on-premises. For the old-schoolers out there, you’ll also learn how to take your existing Dynamics NAV customizations and move them to the new AL language platform. Also, if you haven’t figured it out already, we’re going to be using very normal language throughout the book to keep things light. After all, developing applications is fun, so why not have fun learning as well! What you will learn * Build and deploy Business Central applications * Use the cloud or local sandbox for application development * Customize and extend your base Business Central application * Create external applications that connect to Business Central * Create automated tests and debug your applications * Connect to external web services from Business Central Who this book is for This book is for Dynamics developers and administrators who want to become efficient in developing and deploying applications in Business Central. Basic knowledge and understanding of Dynamics application development and administration is assumed.