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.

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.

Explore Xamarin.Forms to develop dynamic applications Key Features *Explore SQLite through Xamarin to store locations for various location-based applications *Make a real-time serverless chat service by using Azure SignalR service *Build Augmented Reality application with the power of UrhoSharp together with ARKit and ARCore Book Description Xamarin.Forms is a lightweight cross-platform development toolkit for building applications with a rich user interface. In this book you'll start by building projects that explain the Xamarin.Forms ecosystem to get up and running with building cross-platform applications. We'll increase in difficulty throughout the projects, making you learn the nitty-gritty of Xamarin.Forms offerings. You'll gain insights into the architecture, how to arrange your app's design, where to begin developing, what pitfalls exist, and how to avoid them. The book contains seven real-world projects, to get you hands-on with building rich UIs and providing a truly cross-platform experience. It will also guide you on how to set up a machine for Xamarin app development. You'll build a simple to-do application that gets you going, then dive deep into building advanced apps such as messaging platform, games, and machine learning, to build a UI for an augmented reality project. By the end of the book, you'll be confident in building cross-platforms and fitting Xamarin.Forms toolkits in your app development. You'll be able to take the practice you get from this book to build applications that comply with your requirements. What you will learn *Set up a machine for Xamarin development *Get to know about MVVM and data bindings in Xamarin.Forms *Understand how to use custom renderers to gain platform-specific access *Discover Geolocation services through Xamarin Essentials *Create an abstraction of ARKit and ARCore to expose as a single API for the game *Learn how to train a model for image *classification with Azure Cognitive Services Who this book is for This book is for mobile application developers who want to start building native mobile apps using the powerful Xamarin.Forms and C#. Working knowledge of C#, .NET, and Visual Studio is required.

Extend your skills with Odoo 12 to build resourceful and open source business applications Key Features *Explore Odoo 12 capabilities to develop business applications *Program business logic and manipulate data to implement specific business rules in your applications *Integrate Python APIs for building customizable and scalable business logic Book Description Odoo is one of the best platforms for open source ERP and CRM. Its latest version, Odoo 12, brings with it new features and updates in Python packages to develop more customizable applications with additional cloud capabilities. The book begins by covering the development essentials for building business applications. You will start your journey by learning how to install and configure Odoo, and then transition from having no specific knowledge of Odoo to being ready for application development. You will develop your first Odoo application and understand topics such as models and views. Odoo 12 Development Essentials will also guide you in using server APIs to add business logic, helping you lay a solid foundation for advanced topics. As you progress through the chapters, you will be equipped to build and customize your applications and explore the new features in Odoo 12, such as cloud integration, to scale your business applications. You will get insights into building business logic and integrating various APIs into your application. By the end of the book, you will be able to build a business application from scratch by using the latest version of Odoo. What you will learn *Manage Odoo server instances *Create a new Odoo application from scratch using the most frequently used elements *Develop new models and use inheritance to extend existing models *Use ORM methods in the Odoo server and from external clients *Create Kanban views using QWeb effectively *Build custom web and website CMS pages *Use external APIs to integrate Odoo with external applications *Add automated tests and techniques to debug module business logic Who this book is for If you are a developer familiar with Python and MVC design and want to build business applications using Odoo, this book is for you.

Learn to work with XRP and build applications on Ripple's blockchain Key Features *Learn to use Ripple’s decentralized system for transfering digital assets globally *A simpilfied and shortened learning curve to understand the Ripple innovation and Blockchain *Takes a hands-on approach to work with XRP – Ripple’s native currency Book Description This book starts by giving you an understanding of the basics of blockchain and the Ripple protocol. You will then get some hands-on experience of working with XRP. You will learn how to set up a Ripple wallet and see how seamlessly you can transfer money abroad. You will learn about different types of wallets through which you can store and transact XRP, along with the security precautions you need to take to keep your money safe. Since Ripple is currency agnostic, it can enable the transfer of value in USD, EUR, and any other currency. You can even transfer digital assets using Ripple. You will see how you can pay an international merchant with their own native currency and how Ripple can exchange it on the ?y. Once you understand the applications of Ripple, you will learn how to create a conditionally-held escrow using the Ripple API, and how to send and cash checks. Finally, you will also understand the common misconceptions people have about Ripple and discover the potential risks you must consider before making investment decisions. By the end of this book, you will have a solid foundation for working with Ripple's blockchain. Using it, you will be able to solve problems caused by traditional systems in your respective industry. What you will learn *Understand the fundamentals of blockchain and Ripple *Learn how to choose a Ripple wallet *Set up a Ripple wallet to send and receive XRP *Learn how to protect your XRP *Understand the applications of Ripple *Learn how to work with the Ripple API *Learn how to build applications on check and escrow features of Ripple Who this book is for This book is for anyone interested in getting their hands on Ripple technology and learn where it can be used to gain competitive advantages in their respective fields. For most parts of the book, you need not have any pre-requisite knowledge. However, you need to have basic background of JavaScript to write an escrow.

Leverage the power of Python, Ansible and other network automation tools to make your network robust and more secure Key Features *Get introduced to the concept of network automation with relevant use cases *Apply Continuous Integration and DevOps to improve your network performance *Implement effective automation using tools such as Python, Ansible, and more Book Description Network automation is the use of IT controls to supervise and carry out everyday network management functions. It plays a key role in network virtualization technologies and network functions. The book starts by providing an introduction to network automation, and its applications, which include integrating DevOps tools to automate the network efficiently. It then guides you through different network automation tasks and covers various data digging and performing tasks such as ensuring golden state configurations using templates, interface parsing. This book also focuses on Intelligent Operations using Artificial Intelligence and troubleshooting using chatbots and voice commands. The book then moves on to the use of Python and the management of SSH keys for machine-to-machine (M2M) communication, all followed by practical use cases. The book also covers the importance of Ansible for network automation, including best practices in automation; ways to test automated networks using tools such as Puppet, SaltStack, and Chef; and other important techniques. Through practical use-cases and examples, this book will acquaint you with the various aspects of network automation. It will give you the solid foundation you need to automate your own network without any hassle. What you will learn *Get started with the fundamental concepts of network automation *Perform intelligent data mining and remediation based on triggers *Understand how AIOps works in operations *Trigger automation through data factors *Improve your data center's robustness and security through data digging *Get access infrastructure through API Framework for chatbot and voice interactive troubleshootings *Set up communication with SSH-based devices using Netmiko Who this book is for If you are a network engineer or a DevOps professional looking for an extensive guide to help you automate and manage your network efficiently, then this book is for you. No prior experience with network automation is required to get started, however you will need some exposure to Python programming to get the most out of this book.

Learn how some Go-specific language features help to simplify building web scrapers along with common pitfalls and best practices regarding web scraping. Key Features * Use Go libraries like Goquery and Colly to scrape the web * Common pitfalls and best practices to effectively scrape and crawl * Learn how to scrape using the Go concurrency model Book Description Web scraping is the process of extracting information from the web using various tools that perform scraping and crawling. Go is emerging as the language of choice for scraping using a variety of libraries. This book will quickly explain to you, how to scrape data data from various websites using Go libraries such as Colly and Goquery. The book starts with an introduction to the use cases of building a web scraper and the main features of the Go programming language, along with setting up a Go environment. It then moves on to HTTP requests and responses and talks about how Go handles them. You will also learn about a number of basic web scraping etiquettes. You will be taught how to navigate through a website, using a breadth-first and then a depth-first search, as well as find and follow links. You will get to know about the ways to track history in order to avoid loops and to protect your web scraper using proxies. Finally the book will cover the Go concurrency model, and how to run scrapers in parallel, along with large-scale distributed web scraping. What you will learn * Implement Cache-Control to avoid unnecessary network calls * Coordinate concurrent scrapers * Design a custom, larger-scale scraping system * Scrape basic HTML pages with Colly and JavaScript pages with chromedp * Discover how to search using the "strings" and "regexp" packages * Set up a Go development environment * Retrieve information from an HTML document * Protect your web scraper from being blocked by using proxies * Control web browsers to scrape JavaScript sites Who this book is for Data scientists, and web developers with a basic knowledge of Golang wanting to collect web data and analyze them for effective reporting and visualization.

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

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

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

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

Learn how you can control LEDs, make music, and read sensor data using popular microcontrollers such as Adafruit Circuit Playground, ESP8266, and the BBC micro:bit Key Features * Load and execute your first program with MicroPython * Program an IoT device to retrieve weather data using a RESTful API * Get to grips with integrating hardware, programming, and networking concepts with MicroPython Book Description MicroPython is an open source implementation of Python 3 that runs in embedded environments. With MicroPython, you can write clean and simple Python code to control hardware instead of using complex low-level languages like C and C++. This book guides you through all the major applications of the MicroPython platform to build and program projects that use microcontrollers. The MicroPython book covers recipes that’ll help you experiment with the programming environment and hardware programmed in MicroPython. You’ll find tips and techniques for building a variety of objects and prototypes that can sense and respond to touch, sound, position, heat, and light. This book will take you through the uses of MicroPython with a variety of popular input devices and sensors. You’ll learn techniques for handling time delays and sensor readings, and apply advanced coding techniques to create complex projects. As you advance, you’ll get to deal with Internet of Things (IoT) devices and integration with other online web services. Furthermore, you'll also use MicroPython to make music with bananas and create portable multiplayer video games that incorporate sound and light animations into the game play. By the end of the book, you'll have mastered tips and tricks to troubleshoot your development problems and push your MicroPython project to the next level! What you will learn * Execute code without any need for compiling or uploading using REPL (read-evaluate-print-loop) * Program and control LED matrix and NeoPixel drivers to display patterns and colors * Build projects that make use of light, temperature, and touch sensors * Configure devices to create Wi-Fi access points and use network modules to scan and connect to existing networks * Use Pulse Width Modulation to control DC motors and servos * Build an IoT device to display live weather data from the Internet at the touch of a button Who this book is for If you want to build and program projects that use microcontrollers, this book will offer you dozens of recipes to guide you through all the major applications of the MicroPython platform. Although no knowledge of MicroPython or microcontrollers is expected, a general understanding of Python is necessary to get started with this book.

An advanced guide to creating powerful high-performance GUIs for modern, media-rich applications in various domains such as business and game development Key Features * Gain comprehensive knowledge of Python GUI development using PyQt 5.12 * Explore advanced topics including multithreaded programming, 3D animation, and SQL databases * Build cross-platform GUIs for Windows, macOS, Linux, and Raspberry Pi Book Description PyQt5 has long been the most powerful and comprehensive GUI framework available for Python, yet there is a lack of cohesive resources available to teach Python programmers how to use it. This book aims to remedy the problem by providing comprehensive coverage of GUI development with PyQt5. You will get started with an introduction to PyQt5, before going on to develop stunning GUIs with modern features. You will then learn how to build forms using QWidgets and learn about important aspects of GUI development such as layouts, size policies, and event-driven programming. Moving ahead, you’ll discover PyQt5’s most powerful features through chapters on audio-visual programming with QtMultimedia, database-driven software with QtSQL, and web browsing with QtWebEngine. Next, in-depth coverage of multithreading and asynchronous programming will help you run tasks asynchronously and build high-concurrency processes with ease. In later chapters, you’ll gain insights into QOpenGLWidget, along with mastering techniques for creating 2D graphics with QPainter. You’ll also explore PyQt on a Raspberry Pi and interface it with remote systems using QtNetwork. Finally, you will learn how to distribute your applications using setuptools and PyInstaller. By the end of this book, you will have the skills you need to develop robust GUI applications using PyQt. What you will learn * Get to grips with the inner workings of PyQt5 * Learn how elements in a GUI application communicate with signals and slots * Learn techniques for styling an application * Explore database-driven applications with the QtSQL module * Create 2D graphics with QPainter * Delve into 3D graphics with QOpenGLWidget * Build network and web-aware applications with QtNetwork and QtWebEngine Who this book is for This book is for programmers who want to create attractive, functional, and powerful GUIs using the Python language. You’ll also find this book useful if you are a student, professional, or anyone who wants to start exploring GUIs or take your skills to the next level. Although prior knowledge of the Python language is assumed, experience with PyQt, Qt, or GUI programming is not required.

Design and create neural networks with deep learning and artificial intelligence principles using OpenAI Gym, TensorFlow, and Keras Key Features * Explore neural network architecture and understand how it functions * Learn algorithms to solve common problems using back propagation and perceptrons * Understand how to apply neural networks to applications with the help of useful illustrations Book Description Neural networks play a very important role in deep learning and artificial intelligence (AI), with applications in a wide variety of domains, right from medical diagnosis, to financial forecasting, and even machine diagnostics. Hands-On Neural Networks is designed to guide you through learning about neural networks in a practical way. The book will get you started by giving you a brief introduction to perceptron networks. You will then gain insights into machine learning and also understand what the future of AI could look like. Next, you will study how embeddings can be used to process textual data and the role of long short-term memory networks (LSTMs) in helping you solve common natural language processing (NLP) problems. The later chapters will demonstrate how you can implement advanced concepts including transfer learning, generative adversarial networks (GANs), autoencoders, and reinforcement learning. Finally, you can look forward to further content on the latest advancements in the field of neural networks. By the end of this book, you will have the skills you need to build, train, and optimize your own neural network model that can be used to provide predictable solutions. What you will learn * Learn how to train a network by using backpropagation * Discover how to load and transform images for use in neural networks * Study how neural networks can be applied to a varied set of applications * Solve common challenges faced in neural network development * Understand the transfer learning concept to solve tasks using Keras and Visual Geometry Group (VGG) network * Get up to speed with advanced and complex deep learning concepts like LSTMs and NLP * Explore innovative algorithms like GANs and deep reinforcement learning Who this book is for If you are interested in artificial intelligence and deep learning and want to further your skills, then this intermediate-level book is for you. Some knowledge of statistics will help you get the most out of this book.

A practical guide to building high performance systems for object detection, segmentation, video processing, smartphone applications, and more. This book is based on the alpha version of TensorFlow 2. Key Features * Discover how to build, train, and serve your own deep neural networks with TensorFlow 2 and Keras * Apply modern solutions to a wide range of applications such as object detection and video analysis * Learn how to run your models on mobile devices and webpages and improve their performance Book Description Computer vision solutions are becoming increasingly common, making their way in fields such as health, automobile, social media, and robotics. This book will help you explore TensorFlow 2, the brand new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. Hands-On Computer Vision with TensorFlow 2 starts with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface, and move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the book demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build Generative Adversarial Networks (GANs) and Variational Auto-Encoders (VAEs) to create and edit images, and LSTMs to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. By the end of the book, you will have both the theoretical understanding and practical skills to solve advanced computer vision problems with TensorFlow 2.0. What you will learn * Create your own neural networks from scratch * Classify images with modern architectures including Inception and ResNet * Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net * Tackle problems in developing self-driving cars and facial emotion recognition systems * Boost your application’s performance with transfer learning, GANs, and domain adaptation * Use recurrent neural networks for video analysis * Optimize and deploy your networks on mobile devices and in the browser Who this book is for If you’re new to deep learning and have some background in Python programming and image processing, like reading/writing image files and editing pixels, this book is for you. Even if you’re an expert curious about the new TensorFlow 2 features, you’ll find this book useful. While some theoretical explanations require knowledge in algebra and calculus, the book covers concrete examples for learners focused on practical applications such as visual recognition for self-driving cars and smartphone apps.

Build and train scalable neural network models on various platforms by leveraging the power of Caffe2 Key Features * Migrate models trained with other deep learning frameworks on Caffe2 * Integrate Caffe2 with Android or iOS and implement deep learning models for mobile devices * Leverage the distributed capabilities of Caffe2 to build models that scale easily Book Description Caffe2 is a popular deep learning library used for fast and scalable training and inference of deep learning models on various platforms. This book introduces you to the Caffe2 framework and shows how you can leverage its power to build, train, and deploy efficient neural network models at scale. It will cover the topics of installing Caffe2, composing networks using its operators, training models, and deploying models to different architectures. It will also show how to import models from Caffe and from other frameworks using the ONNX interchange format. It covers the topic of deep learning accelerators such as CPU and GPU and shows how to deploy Caffe2 models for inference on accelerators using inference engines. Caffe2 is built for deployment to a diverse set of hardware, using containers on the cloud and resource constrained hardware such as Raspberry Pi, which will be demonstrated. By the end of this book, you will be able to not only compose and train popular neural network models with Caffe2, but also be able to deploy them on accelerators, to the cloud and on resource constrained platforms such as mobile and embedded hardware. What you will learn * Build and install Caffe2 * Compose neural networks * Train neural network on CPU or GPU * Import a neural network from Caffe * Import deep learning models from other frameworks * Deploy models on CPU or GPU accelerators using inference engines * Deploy models at the edge and in the cloud Who this book is for Data scientists and machine learning engineers who wish to create fast and scalable deep learning models in Caffe2 will find this book to be very useful. Some understanding of the basic machine learning concepts and prior exposure to programming languages like C++ and Python will be useful.

Learn end-to-end automation testing techniques for web and mobile browsers using Selenium WebDriver, AppiumDriver, Java, and TestNG Key Features * Explore the Selenium grid architecture and build your own grid for browser and mobile devices * Use ExtentReports for processing results and SauceLabs for cloud-based test services * Unlock the full potential of Selenium to test your web applications. Book Description Selenium WebDriver 3.x is an open source API for testing both browser and mobile applications. With the help of this book, you can build a solid foundation and can easily perform end-to-end testing on web and mobile browsers.You'll begin by being introduced to the Selenium Page Object Model for software development. You'll architect your own framework with a scalable driver class, Java utility classes, and support for third-party tools and plugins. You'll design and build a Selenium grid from scratch to enable the framework to scale and support different browsers, mobile devices, and platforms.You'll strategize and handle a rich web UI using the advanced WebDriver API and learn techniques to handle real-time challenges in WebDriver. You'll perform different types of testing, such as cross-browser testing, load testing, and mobile testing. Finally, you will also be introduced to data-driven testing, using TestNG to create your own automation framework.By the end of this Learning Path, you'll be able to design your own automation testing framework and perform data-driven testing with Selenium WebDriver. This Learning Path includes content from the following Packt products: * Selenium WebDriver 3 Practical Guide - Second Edition by Unmesh Gundecha * Selenium Framework Design in Data-Driven Testing by Carl Cocchiaro What you will learn * Use different mobile and desktop browser platforms with Selenium 3 * Use the Actions API for performing various keyboard and mouse actions * Design the Selenium Driver Class for local, remote, and third-party grid support * Build page object classes with the Selenium Page Object Model * Develop data-driven test classes using the TestNG framework * Encapsulate data using the JSON protocol * Build a Selenium Grid for RemoteWebDriver testing * Build and use utility classes in synchronization, file I/O, reporting and test listener classes Who this book is for This Learning Path is ideal for software quality assurance/testing professionals, software project managers, or software developers interested in using Selenium for testing their applications. Professionals responsible for designing and building enterprise-based testing frameworks will also find this Learning Path useful. Prior programming experience in Java are TestNG is necessary.

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.

Practical solutions to overcome challenges in creating console and web applications and working with systems-level and embedded code, network programming, deep neural networks, and much more. Key Features * Work through recipes featuring advanced concepts such as concurrency, unsafe code, and macros to migrate your codebase to the Rust programming language * Learn how to run machine learning models with Rust * Explore error handling, macros, and modularization to write maintainable code Book Description Rust 2018, Rust's first major milestone since version 1.0, brings more advancement in the Rust language. The Rust Programming Cookbook is a practical guide to help you overcome challenges when writing Rust code. This Rust book covers recipes for configuring Rust for different environments and architectural designs, and provides solutions to practical problems. It will also take you through Rust's core concepts, enabling you to create efficient, high-performance applications that use features such as zero-cost abstractions and improved memory management. As you progress, you'll delve into more advanced topics, including channels and actors, for building scalable, production-grade applications, and even get to grips with error handling, macros, and modularization to write maintainable code. You will then learn how to overcome common roadblocks when using Rust for systems programming, IoT, web development, and network programming. Finally, you'll discover what Rust 2018 has to offer for embedded programmers. By the end of the book, you'll have learned how to build fast and safe applications and services using Rust. What you will learn * Understand how Rust provides unique solutions to solve system programming language problems * Grasp the core concepts of Rust to develop fast and safe applications * Explore the possibility of integrating Rust units into existing applications for improved efficiency * Discover how to achieve better parallelism and security with Rust * Write Python extensions in Rust * Compile external assembly files and use the Foreign Function Interface (FFI) * Build web applications and services using Rust for high performance Who this book is for The Rust cookbook is for software developers looking to enhance their knowledge of Rust and leverage its features using modern programming practices. Familiarity with Rust language is expected to get the most out of this book.

Simplify your DevOps roles with DevOps tools and techniques Key Features * Learn to utilize business resources effectively to increase productivity and collaboration * Leverage the ultimate open source DevOps tools to achieve continuous integration and continuous delivery (CI/CD) * Ensure faster time-to-market by reducing overall lead time and deployment downtime Book Description The implementation of DevOps processes requires the efficient use of various tools, and the choice of these tools is crucial for the sustainability of projects and collaboration between development (Dev) and operations (Ops). This book presents the different patterns and tools that you can use to provision and configure an infrastructure in the cloud. You'll begin by understanding DevOps culture, the application of DevOps in cloud infrastructure, provisioning with Terraform, configuration with Ansible, and image building with Packer. You'll then be taken through source code versioning with Git and the construction of a DevOps CI/CD pipeline using Jenkins, GitLab CI, and Azure Pipelines. This DevOps handbook will also guide you in containerizing and deploying your applications with Docker and Kubernetes. You'll learn how to reduce deployment downtime with blue-green deployment and the feature flags technique, and study DevOps practices for open source projects. Finally, you'll grasp some best practices for reducing the overall application lead time to ensure faster time to market. By the end of this book, you'll have built a solid foundation in DevOps, and developed the skills necessary to enhance a traditional software delivery process using modern software delivery tools and techniques What you will learn * Become well versed with DevOps culture and its practices * Use Terraform and Packer for cloud infrastructure provisioning * Implement Ansible for infrastructure configuration * Use basic Git commands and understand the Git flow process * Build a DevOps pipeline with Jenkins, Azure Pipelines, and GitLab CI * Containerize your applications with Docker and Kubernetes * Check application quality with SonarQube and Postman * Protect DevOps processes and applications using DevSecOps tools Who this book is for If you are a developer or a system administrator interested in understanding continuous integration, continuous delivery, and containerization with DevOps tools and techniques, this book is for you.