Over 30 recipes to develop custom drivers for your embedded Linux applications. Key Features * Use Kernel facilities to develop powerful drivers * Via a practical approach, learn core concepts of developing device drivers * Program a custom character device to get access to kernel internals Book Description Linux is a unified kernel that is widely used to develop embedded systems. As Linux has turned out to be one of the most popular operating systems used, the interest in developing proprietary device drivers has also increased. Device drivers play a critical role in how the system performs and ensures that the device works in the manner intended. By offering several examples on the development of character devices and how to use other kernel internals, such as interrupts, kernel timers, and wait queue, as well as how to manage a device tree, you will be able to add proper management for custom peripherals to your embedded system. You will begin by installing the Linux kernel and then configuring it. Once you have installed the system, you will learn to use the different kernel features and the character drivers. You will also cover interrupts in-depth and how you can manage them. Later, you will get into the kernel internals required for developing applications. Next, you will implement advanced character drivers and also become an expert in writing important Linux device drivers. By the end of the book, you will be able to easily write a custom character driver and kernel code as per your requirements. What you will learn * Become familiar with the latest kernel releases (4.19+/5.x) running on the ESPRESSObin devkit, an ARM 64-bit machine * Download, configure, modify, and build kernel sources * Add and remove a device driver or a module from the kernel * Master kernel programming * Understand how to implement character drivers to manage different kinds of computer peripherals * Become well versed with kernel helper functions and objects that can be used to build kernel applications * Acquire a knowledge of in-depth concepts to manage custom hardware with Linux from both the kernel and user space Who this book is for This book will help anyone who wants to develop their own Linux device drivers for embedded systems. Having basic hand-on with Linux operating system and embedded concepts is necessary.

A beginner's guide to storing, managing, and analyzing data with the updated features of Elastic 7.0 Key Features * Gain access to new features and updates introduced in Elastic Stack 7.0 * Grasp the fundamentals of Elastic Stack including Elasticsearch, Logstash, and Kibana * Explore useful tips for using Elastic Cloud and deploying Elastic Stack in production environments Book Description The Elastic Stack is a powerful combination of tools for techniques such as distributed search, analytics, logging, and visualization of data. Elastic Stack 7.0 encompasses new features and capabilities that will enable you to find unique insights into analytics using these techniques. This book will give you a fundamental understanding of what the stack is all about, and help you use it efficiently to build powerful real-time data processing applications. The first few sections of the book will help you understand how to set up the stack by installing tools, and exploring their basic configurations. You’ll then get up to speed with using Elasticsearch for distributed searching and analytics, Logstash for logging, and Kibana for data visualization. As you work through the book, you will discover the technique of creating custom plugins using Kibana and Beats. This is followed by coverage of the Elastic X-Pack, a useful extension for effective security and monitoring. You’ll also find helpful tips on how to use Elastic Cloud and deploy Elastic Stack in production environments. By the end of this book, you’ll be well versed with the fundamental Elastic Stack functionalities and the role of each component in the stack to solve different data processing problems. What you will learn * Install and configure an Elasticsearch architecture * Solve the full-text search problem with Elasticsearch * Discover powerful analytics capabilities through aggregations using Elasticsearch * Build a data pipeline to transfer data from a variety of sources into Elasticsearch for analysis * Create interactive dashboards for effective storytelling with your data using Kibana * Learn how to secure, monitor and use Elastic Stack’s alerting and reporting capabilities * Take applications to an on-premise or cloud-based production environment with Elastic Stack Who this book is for This book is for entry-level data professionals, software engineers, e-commerce developers, and full-stack developers who want to learn about Elastic Stack and how the real-time processing and search engine works for business analytics and enterprise search applications. Previous experience with Elastic Stack is not required, however knowledge of data warehousing and database concepts will be helpful.

Evade antiviruses and bypass firewalls with the most widely used penetration testing frameworks Key Features * Gain insights into the latest antivirus evasion techniques * Set up a complete pentesting environment using Metasploit and virtual machines * Discover a variety of tools and techniques that can be used with Kali Linux Book Description Penetration testing or ethical hacking is a legal and foolproof way to identify vulnerabilities in your system. With thorough penetration testing, you can secure your system against the majority of threats. This Learning Path starts with an in-depth explanation of what hacking and penetration testing is. You’ll gain a deep understanding of classical SQL and command injection flaws, and discover ways to exploit these flaws to secure your system. You'll also learn how to create and customize payloads to evade antivirus software and bypass an organization's defenses. Whether it’s exploiting server vulnerabilities and attacking client systems, or compromising mobile phones and installing backdoors, this Learning Path will guide you through all this and more to improve your defense against online attacks. By the end of this Learning Path, you'll have the knowledge and skills you need to invade a system and identify all its vulnerabilities. This Learning Path includes content from the following Packt products: * Web Penetration Testing with Kali Linux - Third Edition by Juned Ahmed Ansari and Gilberto Najera-Gutierrez * Metasploit Penetration Testing Cookbook - Third Edition by Abhinav Singh , Monika Agarwal, et al What you will learn * Build and analyze Metasploit modules in Ruby * Integrate Metasploit with other penetration testing tools * Use server-side attacks to detect vulnerabilities in web servers and their applications * Explore automated attacks such as fuzzing web applications * Identify the difference between hacking a web application and network hacking * Deploy Metasploit with the Penetration Testing Execution Standard (PTES) * Use MSFvenom to generate payloads and backdoor files, and create shellcode Who this book is for This Learning Path is designed for security professionals, web programmers, and pentesters who want to learn vulnerability exploitation and make the most of the Metasploit framework. Some understanding of penetration testing and Metasploit is required, but basic system administration skills and the ability to read code are a must.

Discover various techniques to develop maintainable code and keep it in shape. Key Features * Learn all about refactoring - why it is important and how to do it * Discover easy ways to refactor code with examples * Explore techniques that can be applied to most other programming languages Book Description Refactoring improves your code without changing its behavior. With refactoring, the best approach is to apply small targeted changes to a codebase. Instead of doing a huge sweeping change to your code, refactoring is better as a long-term and continuous enterprise. Refactoring TypeScript explains how to spot bugs and remove them from your code. You’ll start by seeing how wordy conditionals, methods, and null checks make code unhealthy and unstable. Whether it is identifying messy nested conditionals or removing unnecessary methods, this book will show various techniques to avoid these pitfalls and write code that is easier to understand, maintain, and test. By the end of the book, you’ll have learned some of the main causes of unhealthy code, tips to identify them and techniques to address them. What you will learn * Spot and fix common code smells to create code that is easier to read and understand * Discover ways to identify long methods and refactor them * Create objects that keep your code flexible, maintainable, and testable * Apply the Single Responsibility Principle to develop less-coupled code * Discover how to combine different refactoring techniques * Learn ways to solve the issues caused by overusing primitives Who this book is for This book is designed for programmers who are looking to explore various refactoring techniques to develop healthy and maintainable code. Some experience in JavaScript and TypeScript can help you easily grasp the concepts explained in this book.

Leverage PowerShell to perform many day-to-day tasks in Microsoft Azure Key Features *Deploy and manage Azure virtual machines with PowerShell commands. *Get to grips with core concept of Azure PowerShell such as working with images and disks, custom script extension, high availability and more. *Leverage hands-on projects to successfully apply what you learned through the course of this book. Book Description As an IT professional, it is important to keep up with cloud technologies and learn to manage those technologies. PowerShell is a critical tool that must be learned in order to effectively and more easily manage many Azure resources. This book is designed to teach you to leverage PowerShell to enable you to perform many day-to-day tasks in Microsoft Azure. Taking you through the basic tasks of installing Azure PowerShell and connecting to Azure, you will learn to properly connect to an Azure tenant with PowerShell. Next, you will dive into tasks such as deploying virtual machines with PowerShell, resizing them, and managing their power states with PowerShell. Then, you will learn how to complete more complex Azure tasks with PowerShell, such as deploying virtual machines from custom images, creating images from existing virtual machines, and creating and managing of data disks. Later, you will learn how to snapshot virtual machines, how to encrypt virtual machines, and how to leverage load balancers to ensure high availability with PowerShell. By the end of this book, you will have developed dozens of PowerShell skills that are invaluable in the deployment and management of Azure virtual machines. What you will learn *Manage virtual machines with PowerShell *Resize a virtual machine with PowerShell *Create OS disk snapshots via PowerShell *Deploy new virtual machines from snapshots via PowerShell *Provision and attach data disks to a virtual machine via PowerShell *Load balance virtual machines with PowerShell *Manage virtual machines with custom script extensions Who this book is for This book is intended for IT professionals who are responsible for managing Azure virtual machines. No prior PowerShell or Azure experience is needed.

Learn development skills and improve productivity when programming in Microsoft Dynamics NAV 2018 - the popular Enterprise Resourse Planning management system used across a variety of industries for business process management Key Features *Solve common business problems with the valuable features and flexibility of Dynamics NAV *Understand the structure of NAV database - how documents and business entities are mapped to DB tables *Design user interface and bind the presentation layer with the data storage Book Description Microsoft Dynamics NAV is an enterprise resource planning (ERP) software suite for organizations. The system offers specialized functionality for manufacturing, distribution, government, retail, and other industries. This book gets you started with its integrated development environment for solving problems by customizing business processes. This book introduces the NAV development environment – C/SIDE. It gives an overview of the internal system language and the most essential development tools. The book will enable the reader to customize and extend NAV functionality with C/AL code, design a user interface through pages, create role centers, and build advanced reports in Microsoft Visual Studio. By the end of the book, you will have learned how to extend the NAV data model, how to write and debug custom code, and how to exchange data with external applications. What you will learn *Manage NAV Server configuration with Microsoft Management Console *Manage NAV installation with the NAV Administration Shell *Create integration events and extend functionality via the NAV event model *Run XML Ports from C/AL code *Design reports and write client code in RDLC expressions Who this book is for This book is for experienced NAV users who have an understanding of basic programming concepts. Familiarity with NAV development environment or its internal development language-C/AL is not expected.

Architect scalable, reliable, and maintainable applications for enterprises with Python Key Features *Explore various Python design patterns used for enterprise software development *Apply best practices for testing and performance optimization to build stable applications *Learn about different attacking strategies used on enterprise applications and how to avoid them Book Description Dynamically typed languages like Python are continuously improving. With the addition of exciting new features and a wide selection of modern libraries and frameworks, Python has emerged as an ideal language for developing enterprise applications. Hands-On Enterprise Application Development with Python will show you how to build effective applications that are stable, secure, and easily scalable. The book is a detailed guide to building an end-to-end enterprise-grade application in Python. You will learn how to effectively implement Python features and design patterns that will positively impact your application lifecycle. The book also covers advanced concurrency techniques that will help you build a RESTful application with an optimized frontend. Given that security and stability are the foundation for an enterprise application, you’ll be trained on effective testing, performance analysis, and security practices, and understand how to embed them in your codebase during the initial phase. You’ll also be guided in how to move on from a monolithic architecture to one that is service oriented, leveraging microservices and serverless deployment techniques. By the end of the book, you will have become proficient at building efficient enterprise applications in Python. What you will learn *Understand the purpose of design patterns and their impact on application lifecycle *Build applications that can handle large amounts of data-intensive operations *Uncover advanced concurrency techniques and discover how to handle a large number of requests in production *Optimize frontends to improve the client-side experience of your application *Effective testing and performance profiling techniques to detect issues in applications early in the development cycle *Build applications with a focus on security *Implement large applications as microservices to improve scalability Who this book is for If you’re a developer who wants to build enterprise-grade applications, this book is for you. Basic to intermediate-level of programming experience with Python and database systems is required to understand the concepts covered in this book.

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

Explore powerful Azure DevOps solutions to develop and deploy your software faster and more efficiently. Key Features * Build modern microservice-based systems with Azure architecture * Learn to deploy and manage cloud services and virtual machines * Configure clusters with Azure Service Fabric for deployment Book Description This Learning Path helps you understand microservices architecture and leverage various services of Microsoft Azure Service Fabric to build, deploy, and maintain highly scalable enterprise-grade applications. You will learn to select an appropriate Azure backend structure for your solutions and work with its toolkit and managed apps to share your solutions with its service catalog. As you progress through the Learning Path, you will study Azure Cloud Services, Azure-managed Kubernetes, and Azure Container Services deployment techniques. To apply all that you’ve understood, you will build an end-to-end Azure system in scalable, decoupled tiers for an industrial bakery with three business domains. Toward the end of this Learning Path, you will build another scalable architecture using Azure Service Bus topics to send orders between decoupled business domains with scalable worker roles processing these orders. By the end of this Learning Path, you will be comfortable in using development, deployment, and maintenance processes to build robust cloud solutions on Azure. This Learning Path includes content from the following Packt products: * Learn Microsoft Azure by Mohamed Wali * Implementing Azure Solutions - Second Edition by Florian Klaffenbach, Oliver Michalski, Markus Klein * Microservices with Azure by Namit Tanasseri and Rahul Rai What you will learn * Study various Azure Service Fabric application programming models * Create and manage a Kubernetes cluster in Azure Kubernetes Service * Use site-to-site VPN and ExpressRoute connections in your environment * Design an Azure IoT app and learn to operate it in various scenarios * Implement a hybrid Azure design using Azure Stack * Build Azure SQL databases with Code First Migrations * Integrate client applications with Web API and SignalR on Azure * Implement the Azure Active Directory (Azure AD) across the entire system Who this book is for If you are an IT system architect, network admin, or a DevOps engineer who wants to implement Azure solutions for your organization, this Learning Path is for you. Basic knowledge of the Azure Cloud platform will be beneficial.

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

Your hands-on reference guide to developing, training, and optimizing your machine learning models Key Features * Your guide to learning efficient machine learning processes from scratch * Explore expert techniques and hacks for a variety of machine learning concepts * Write effective code in R, Python, Scala, and Spark to solve all your machine learning problems Book Description Machine learning makes it possible to learn about the unknowns and gain hidden insights into your datasets by mastering many tools and techniques. This book guides you to do just that in a very compact manner. After giving a quick overview of what machine learning is all about, Machine Learning Quick Reference jumps right into its core algorithms and demonstrates how they can be applied to real-world scenarios. From model evaluation to optimizing their performance, this book will introduce you to the best practices in machine learning. Furthermore, you will also look at the more advanced aspects such as training neural networks and work with different kinds of data, such as text, time-series, and sequential data. Advanced methods and techniques such as causal inference, deep Gaussian processes, and more are also covered. By the end of this book, you will be able to train fast, accurate machine learning models at your fingertips, which you can easily use as a point of reference. What you will learn * Get a quick rundown of model selection, statistical modeling, and cross-validation * Choose the best machine learning algorithm to solve your problem * Explore kernel learning, neural networks, and time-series analysis * Train deep learning models and optimize them for maximum performance * Briefly cover Bayesian techniques and sentiment analysis in your NLP solution * Implement probabilistic graphical models and causal inferences * Measure and optimize the performance of your machine learning models Who this book is for If you’re a machine learning practitioner, data scientist, machine learning developer, or engineer, this book will serve as a reference point in building machine learning solutions. You will also find this book useful if you’re an intermediate machine learning developer or data scientist looking for a quick, handy reference to all the concepts of machine learning. You’ll need some exposure to machine learning to get the best out of this book.

Discover a project-based approach to mastering machine learning concepts by applying them to everyday problems using libraries such as scikit-learn, TensorFlow, and Keras Key Features * Get to grips with Python's machine learning libraries including scikit-learn, TensorFlow, and Keras * Implement advanced concepts and popular machine learning algorithms in real-world projects * Build analytics, computer vision, and neural network projects Book Description Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to put your knowledge and skills into practice and use the Python ecosystem to cover key domains in machine learning. This second edition covers a range of libraries from the Python ecosystem, including TensorFlow and Keras, to help you implement real-world machine learning projects. The book begins by giving you an overview of machine learning with Python. With the help of complex datasets and optimized techniques, you’ll go on to understand how to apply advanced concepts and popular machine learning algorithms to real-world projects. Next, you’ll cover projects from domains such as predictive analytics to analyze the stock market and recommendation systems for GitHub repositories. In addition to this, you’ll also work on projects from the NLP domain to create a custom news feed using frameworks such as scikit-learn, TensorFlow, and Keras. Following this, you’ll learn how to build an advanced chatbot, and scale things up using PySpark. In the concluding chapters, you can look forward to exciting insights into deep learning and you'll even create an application using computer vision and neural networks. By the end of this book, you’ll be able to analyze data seamlessly and make a powerful impact through your projects. What you will learn * Understand the Python data science stack and commonly used algorithms * Build a model to forecast the performance of an Initial Public Offering (IPO) over an initial discrete trading window * Understand NLP concepts by creating a custom news feed * Create applications that will recommend GitHub repositories based on ones you’ve starred, watched, or forked * Gain the skills to build a chatbot from scratch using PySpark * Develop a market-prediction app using stock data * Delve into advanced concepts such as computer vision, neural networks, and deep learning Who this book is for This book is for machine learning practitioners, data scientists, and deep learning enthusiasts who want to take their machine learning skills to the next level by building real-world projects. The intermediate-level guide will help you to implement libraries from the Python ecosystem to build a variety of projects addressing various machine learning domains. Knowledge of Python programming and machine learning concepts will be helpful.

Understand, design, and create cognitive applications using Watson’s suite of APIs. Key Features * Develop your skills and work with IBM Watson APIs to build efficient and powerful cognitive apps * Learn how to build smart apps to carry out different sets of activities using real-world use cases * Get well versed with the best practices of IBM Watson and implement them in your daily work Book Description Cognitive computing is rapidly infusing every aspect of our lives riding on three important fields: data science, machine learning (ML), and artificial intelligence (AI). It allows computing systems to learn and keep on improving as the amount of data in the system grows. This book introduces readers to a whole new paradigm of computing – a paradigm that is totally different from the conventional computing of the Information Age. You will learn the concepts of ML, deep learning (DL), neural networks, and AI through the set of APIs provided by IBM Watson. This book will help you build your own applications to understand, plan, and solve problems, and analyze them as per your needs. You will learn about various domains of cognitive computing, such as NLP, voice processing, computer vision, emotion analytics, and conversational systems, using different IBM Watson APIs. From this, the reader will learn what ML is, and what goes on in the background to make computers "do their magic," as well as where these concepts have been applied. Having achieved this, the readers will then be able to embark on their journey of learning, researching, and applying the concept in their respective fields. What you will learn * Get well versed with the APIs provided by IBM Watson on IBM Cloud * Learn ML, AI, cognitive computing, and neural network principles * Implement smart applications in fields such as healthcare, entertainment, security, and more * Understand unstructured content using cognitive metadata with the help of Natural Language Understanding * Use Watson’s APIs to create real-life applications to realize their capabilities * Delve into various domains of cognitive computing, such as media analytics, embedded deep learning, computer vision, and more Who this book is for This book is for beginners and novices; having some knowledge about artificial intelligence and deep learning is an advantage, but not a prerequisite to benefit from this book. We explain the concept of deep learning and artificial intelligence through the set of tools IBM Watson provides.

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

All the key deep learning methods built step-by-step in PyTorch Key Features * Understand the internals and principles of PyTorch * Implement key deep learning methods in PyTorch: CNNs, GANs, RNNs, reinforcement learning, and more * Build deep learning workflows and take deep learning models from prototyping to production Book Description PyTorch is a new, lightweight, and Python-first tool for deep learning. Built by Facebook to offer flexibility and speed, it has quickly become the preferred tool for deep learning experts. PyTorch helps you release deep learning models faster than ever before. PyTorch Deep Learning Hands-On shows how to implement every major deep learning architecture in PyTorch. Starting with simple neural networks, it covers PyTorch for computer vision (CNN), natural language processing (RNN), GANs, and reinforcement learning. You will also build deep learning workflows with the PyTorch framework, migrate models built in Python to highly efficient TorchScript, and deploy to production using the most sophisticated available tools. Each chapter focuses on a different area of deep learning. Chapters start with a refresher on the core principles, before sharing the code you need to implement them in PyTorch. If you want to become a deep learning expert this book is for you. What you will learn Use PyTorch to build: * Simple Neural Networks – build neural networks the PyTorch way, with high-level functions, optimizers, and more * Convolutional Neural Networks – create advanced computer vision systems * Recurrent Neural Networks – work with sequential data such as natural language and audio * Generative Adversarial Networks – create new content with models including SimpleGAN and CycleGAN * Reinforcement Learning – develop systems that can solve complex problems such as driving or game playing * Deep Learning workflows – move effectively from ideation to production with proper deep learning workflow using PyTorch and its utility packages * Production-ready models – package your models for high-performance production environments Who this book is for Machine learning professionals and enthusiasts who know Python and want to build efficient and powerful deep learning systems in PyTorch.

Learn a modern approach to data analysis using Python to harness the power of programming and AI across your data. Detailed case studies bring this modern approach to life across visual data, social media, graph algorithms, and time series analysis. Key Features *Bridge your data analysis with the power of programming, complex algorithms, and AI *Use Python and its extensive libraries to power your way to new levels of data insight *Work with AI algorithms, TensorFlow, graph algorithms, NLP, and financial time series *Explore this modern approach across with key industry case studies and hands-on projects Book Description Data Analysis with Python offers a modern approach to data analysis so that you can work with the latest and most powerful Python tools, AI techniques, and open source libraries. Industry expert David Taieb shows you how to bridge data science with the power of programming and algorithms in Python. You'll be working with complex algorithms, and cutting-edge AI in your data analysis. Learn how to analyze data with hands-on examples using Python-based tools and Jupyter Notebook. You'll find the right balance of theory and practice, with extensive code files that you can integrate right into your own data projects. Explore the power of this approach to data analysis by then working with it across key industry case studies. Four fascinating and full projects connect you to the most critical data analysis challenges you’re likely to meet in today. The first of these is an image recognition application with TensorFlow – embracing the importance today of AI in your data analysis. The second industry project analyses social media trends, exploring big data issues and AI approaches to natural language processing. The third case study is a financial portfolio analysis application that engages you with time series analysis - pivotal to many data science applications today. The fourth industry use case dives you into graph algorithms and the power of programming in modern data science. You'll wrap up with a thoughtful look at the future of data science and how it will harness the power of algorithms and artificial intelligence. What you will learn *A new toolset that has been carefully crafted to meet for your data analysis challenges *Full and detailed case studies of the toolset across several of today’s key industry contexts *Become super productive with a new toolset across Python and Jupyter Notebook *Look into the future of data science and which directions to develop your skills next Who this book is for This book is for developers wanting to bridge the gap between them and data scientists. Introducing PixieDust from its creator, the book is a great desk companion for the accomplished Data Scientist. Some fluency in data interpretation and visualization is assumed. It will be helpful to have some knowledge of Python, using Python libraries, and some proficiency in web development.

Take your financial skills to the next level by mastering cutting-edge mathematical and statistical financial applications Key Features * Explore advanced financial models used by the industry and ways of solving them using Python * Build state-of-the-art infrastructure for modeling, visualization, trading, and more * Empower your financial applications by applying machine learning and deep learning Book Description The second edition of Mastering Python for Finance will guide you through carrying out complex financial calculations practiced in the industry of finance by using next-generation methodologies. You will master the Python ecosystem by leveraging publicly available tools to successfully perform research studies and modeling, and learn to manage risks with the help of advanced examples. You will start by setting up your Jupyter notebook to implement the tasks throughout the book. You will learn to make efficient and powerful data-driven financial decisions using popular libraries such as TensorFlow, Keras, Numpy, SciPy, and sklearn. You will also learn how to build financial applications by mastering concepts such as stocks, options, interest rates and their derivatives, and risk analytics using computational methods. With these foundations, you will learn to apply statistical analysis to time series data, and understand how time series data is useful for implementing an event-driven backtesting system and for working with high-frequency data in building an algorithmic trading platform. Finally, you will explore machine learning and deep learning techniques that are applied in finance. By the end of this book, you will be able to apply Python to different paradigms in the financial industry and perform efficient data analysis. What you will learn * Solve linear and nonlinear models representing various financial problems * Perform principal component analysis on the DOW index and its components * Analyze, predict, and forecast stationary and non-stationary time series processes * Create an event-driven backtesting tool and measure your strategies * Build a high-frequency algorithmic trading platform with Python * Replicate the CBOT VIX index with SPX options for studying VIX-based strategies * Perform regression-based and classification-based machine learning tasks for prediction * Use TensorFlow and Keras in deep learning neural network architecture Who this book is for If you are a financial or data analyst or a software developer in the financial industry who is interested in using advanced Python techniques for quantitative methods in finance, this is the book you need! You will also find this book useful if you want to extend the functionalities of your existing financial applications by using smart machine learning techniques. Prior experience in Python is required.

A complete guide to understanding, developing, and testing popular security-token smart contracts Key Features * Understand key Blockchain and Ethereum platforms concepts * Step-by-step guide to developing STO smart contracts on Ethereum * Monetize digital tokens under various U.S. securities laws Book Description The failure of initial coin offerings (ICOs) is no accident, as most ICOs do not link to a real asset and are not regulated. Realizing the shortcomings of ICOs, the blockchain community and potential investors embraced security token offerings (STOs) and stablecoins enthusiastically. In this book, we start with an overview of the blockchain technology along with its basic concepts. We introduce the concept behind STO, and cover the basic requirements for launching a STO and the relevant regulations governing its issuance. We discuss U.S. securities laws development in launching security digital tokens using blockchain technology and show some real use cases. We also explore the process of STO launches and legal considerations. We introduce popular security tokens in the current blockchain space and talk about how to develop a security token DApp, including smart contract development for ERC1404 tokens. Later, you'll learn to build frontend side functionalities to interact with smart contracts. Finally, we discuss stablecoin technical design functionalities for issuing and operating STO tokens by interacting with Ethereum smart contracts. By the end of this book, you will have learned more about STOs and gained a detailed knowledge of building relevant applications—all with the help of practical examples. What you will learn * Understand the basic requirements for launching a security token offering * Explore various US securities laws governing the offering of security digital tokens * Get to grips with the stablecoin concept with the help of use cases * Learn how to develop security token decentralized applications * Understand the difference between ERC-20 and ERC-721 tokens * Learn how to set up a development environment and build security tokens * Explore the technical design of stablecoins Who this book is for This book is ideal for blockchain beginners and business user developers who want to quickly master popular Security Token Offerings and stablecoins. Readers will learn how to develop blockchain/digital cryptos, guided by U.S. securities laws and utilizing some real use cases. Prior exposure to an Object-Oriented Programming language such as JavaScript would be an advantage, but is not mandatory.

Build Vue apps the right way using Vue CLI 3. Understand how the building blocks of Vue CLI 3 work including npm, webpack, babel, eslint, plugins, GUI, testing, and SCSS. Import third-party libraries and maintain your project. Key Features * Learn to work with Vue CLI 3 both on the command line and with a GUI * Manage VueJS apps, settings, Vue plugins, and third-party libraries * Learn how to build Vue apps from scratch using webpack, babel, ES6, vue-router, Jest, Cypress, SCSS, and Git Book Description The sprawling landscape of various tools in JavaScript web development is becoming overwhelming. This book will show you how Vue CLI 3 can help you take back control of the tool chain. To that end, we'll begin by configuring webpack, utilizing HMR, and using single-file .vue components. We'll also use SCSS, ECMAScript, and TypeScript. We'll unit test with Jest and perform E2E testing with Cypress. This book will show you how to configure Vue CLI as your default way of building Vue projects. You'll discover the reasons behind using webpack, babel, eslint, and other modern JavaScript toolchain technologies. You'll learn about the inner workings of each through the lens of Vue CLI 3. We'll explore the extendibility of Vue CLI with the built-in settings, and various core and third-party plugins. Vue CLI helps you work with Vue components, routers, directives, and services in the Vue ecosystem. While learning these concepts, you'll examine the evolution of JavaScript. You'll learn about use of npm, IIFEs, modules in JavaScript, Common.js modules, task runners, npm scripts, module bundlers, and webpack. You'll get familiar with the reasons why Vue CLI 3 is set up the way it is. You'll also learn to perform linting with ESLint and Prettier. Towards the end, we'll introduce you to working with styles and SCSS. Finally, we'll show you how to deploy your very own Vue project on Github Pages. What you will learn * Work with nvm, install Node.js and npm, use Vue CLI 3 with no configuration, via the command line and the graphical user interface * Build a Vue project from scratch using npm and webpack, and learn about hot module replacement * Work with Babel settings, configurations, and presets * Work with Vue plugins, including testing plugins such as Jest and Cypress * Write, run, and watch unit and E2E tests using TDD assertions in the red-green-refactor cycle * Work with Vue router and use, nested, lazy-loading, and dynamic routes * Add SCSS to your projects and work with third-party Vue plugins * Deploy your Vue apps to Github Pages Who this book is for This book is for existing web developers and developers who are new to web development. You must be familiar with HTML, CSS, and JavaScript programming. Basic knowledge of the command line will be helpful but is not necessary.

Leverage the power of Python and statistical modeling techniques for building accurate predictive models Key Features * Get introduced to Python's rich suite of libraries for statistical modeling * Implement regression, clustering and train neural networks from scratch * Includes real-world examples on training end-to-end machine learning systems in Python Book Description Python's ease of use and multi-purpose nature has led it to become the choice of tool for many data scientists and machine learning developers today. Its rich libraries are widely used for data analysis, and more importantly, for building state-of-the-art predictive models. This book takes you through an exciting journey, of using these libraries to implement effective statistical models for predictive analytics. You’ll start by diving into classical statistical analysis, where you will learn to compute descriptive statistics using pandas. You will look at supervised learning, where you will explore the principles of machine learning and train different machine learning models from scratch. You will also work with binary prediction models, such as data classification using k-nearest neighbors, decision trees, and random forests. This book also covers algorithms for regression analysis, such as ridge and lasso regression, and their implementation in Python. You will also learn how neural networks can be trained and deployed for more accurate predictions, and which Python libraries can be used to implement them. By the end of this book, you will have all the knowledge you need to design, build, and deploy enterprise-grade statistical models for machine learning using Python and its rich ecosystem of libraries for predictive analytics. What you will learn * Understand the importance of statistical modeling * Learn about the various Python packages for statistical analysis * Implement algorithms such as Naive Bayes, random forests, and more * Build predictive models from scratch using Python's scikit-learn library * Implement regression analysis and clustering * Learn how to train a neural network in Python Who this book is for If you are a data scientist, a statistician or a machine learning developer looking to train and deploy effective machine learning models using popular statistical techniques, then this book is for you. Knowledge of Python programming is required to get the most out of this book.

A step-by-step guide to learning Flutter and Dart 2 for creating Android and iOS mobile applications Key Features * Get up to speed with the basics of Dart programming and delve into Flutter development * Understand native SDK and third-party libraries for building Android and iOS applications using Flutter * Package and deploy your Flutter apps to achieve native-like performance Book Description Google Flutter is a cross-platform mobile platform that makes it easier to write secure and high-performance native apps for iOS and Android. This book begins by introducing you to the Flutter framework and basics of Dart. You’ll learn to set up the development environment to get started with your Flutter project. The book will guide you through designing the user interface and user input functions for your app. As you progress, you’ll explore the navigator widget to manage your app routes and understand how to add transitions between screens. You’ll then get to grips with developing your own plugin and discover how to structure good plugin code. The book will help you display a map from the Flutter app, add markers and interactions to it, and use the Google Places API. You’ll build on your knowledge by not only adding tests to create a bug-free app, but also preparing it for deployment on Apple's App Store and Google Play. In later chapters, you’ll learn to improve the user experience with advanced features such as map integrations, platform-specific code with native programming languages, and personalized animation options for designing intuitive UIs. By the end of this book, you’ll be well-versed with Dart programming and have the skills to develop your own mobile apps or build a career as a Dart and Flutter app developer. What you will learn * Understand the fundamentals of the Dart programming language * Explore the core concepts of the Flutter UI and how it compiles for multiple platforms * Develop Flutter plugins and widgets and understand how to structure good plugin code * Style your apps with widgets and learn the difference between stateful and stateless widgets * Add animation to your UI using Flutter's AnimatedBuilder component * Integrate your native code into your Flutter codebase for native app performance Who this book is for This book is for developers looking to learn Google's revolutionary framework, Flutter from scratch. No knowledge of Flutter or Dart is required. However, basic programming language knowledge will be helpful.