Dive and explore into the latest addons of the latest Git.About This Book·Master all the basic concepts of Git to protect your code and make it easier to evolve·Use Git proficiently, and learn how to resolve day-by-day challenges easily·This step-by-step guide is packed with examples to help you learn and work with Git's internalsWho This Book Is ForIf you are a software developer with little or no experience of versioning systems, or you are familiar with other centralized versioning systems, then this book is for you.If you have experience in server and system management and need to broaden your use of Git from a DevOps perspective, this book contains everything you need.What You Will Learn·Master Git fundamentals·Be able to "visualize," even with the help of a valid GUI tool·Write principal commands in a shell·Figure out the right strategy to run change your daily work with few or no annoyances·Explore the tools used to migrate to Git from the Subversion versioning system without losing your development history·Plan new projects and repositories with ease, using online services, or local network resourcesIn DetailSince its inception, Git has attracted skilled developers due to its robust, powerful, and reliable features. Its incredibly fast branching ability transformed a piece of code from a niche tool for Linux Kernel developers into a mainstream distributed versioning system. Like most powerful tools, Git can be hard to approach since it has a lot of commands, subcommands, and options that easily confuse newcomers.The 2nd edition of this very successful book will help you overcome this fear and become adept in all the basic tasks in Git. Building upon the success of the first book, we start with a brief step-by-step installation guide; after this, you'll delve into the essentials of Git. For those of you who have bought the first edition, this time we go into internals in far greater depth, talking less about theory and using much more practical examples.The book serves as a primer for topics to follow, such as branching and merging, creating and managing a GitHub personal repository, and fork and pull requests. You'll then learn the art of cherry-picking, taking only the commits you want, followed by Git blame. Finally, we'll see how to interoperate with a Subversion server, covering the concepts and commands needed to convert an SVN repository into a Git repository.To conclude, this is a collection of resources, links, and appendices to satisfy even the most curious.Style and approachThis short guide will help you understand the concepts and fundamentals of GIT is a step-by-step manner.

☆★☆The Ultimate ?Guide To The World of Bitcoin ?Technology is here! ☆★☆ This book will teach you the history, fundamentals, and real world applications of bitcoin cryptocurrency ?Tired of being cheated by the current system of ?central banking? They are like rouge intermediaries with absolute control and hold all the power and can print money on a whim. How much longer can we allow this dysfunctional system of currency exchange to exist? ?This is the digital age and this new wave of currency will impact the lives of millions and even billions worldwide! ?Meaning ?no more scandals from third party intermediaries who can print money out of thin air! No more centralized banks! But a unified and decentralized system that is transparent, distributed, and validated among EVERYONE. If ?you are wondering how can all this be possible? Than it is strongly recommended you grab your copy now and learn everything you need to know about bitcoin, whether you want to invest or understand the convoluted concepts of cyptocurrency in the most easy to read and detailed step by step guide in plain English! What You'll Learn ?Benefits of Bitcoin ?History of Bitcoin Real World Application ?Blockchain technology ?How mining works ?Estimating Trends ?Worldwide Influence On ?Laws, Policies and Regulations For Bitcoin ?And, much,much more! Not enough? Ok, well there's more... This book also includes bonus chapters and diagrams! ?Over 200+ pages of valuable content! ?How Does This Book Differ From The Rest? ?This book is truly set apart from the rest and is vastly superior. There's an entire section dedicated to blockchain technology as understanding the fundamental technology behind bitcoin is as equally as important itself. Unlike other books this book does not skim over any details, but gives you the reader an enhanced experience of in depth information, so you can have a greater understanding of both bitcoin and blockchain technology. What are you waiting for? Grab your copy now and join the next big wave of change and see the future! ?Imagine a world with no more physical currency or central authority figures that control the supply of money.

Introducing modular techniques for building sophisticated programs using PythonAbout This Book·The book would help you develop succinct, expressive programs using modular deign·The book would explain best practices and common idioms through carefully explained and structured examples·It will have broad appeal as far as target audience is concerned and there would be take away for all beginners to PythonWho This Book Is ForThis book is intended for beginner to intermediate level Python programmers who wish to learn how to use modules and packages within their programs. While readers must understand the basics of Python programming, no knowledge of modular programming techniques is required.What You Will Learn·Learn how to use modules and packages to organize your Python code·Understand how to use the import statement to load modules and packages into your program·Use common module patterns such as abstraction and encapsulation to write better programs·Discover how to create self-testing Python packages·Create reusable modules that other programmers can use·Learn how to use GitHub and the Python Package Index to share your code with other people·Make use of modules and packages that others have written·Use modular techniques to build robust systems that can handle complexity and changing requirements over timeIn DetailPython has evolved over the years and has become the primary choice of developers in various fields. The purpose of this book is to help readers develop readable, reliable, and maintainable programs in Python.Starting with an introduction to the concept of modules and packages, this book shows how you can use these building blocks to organize a complex program into logical parts and make sure those parts are working correctly together.Using clearly written, real-world examples, this book demonstrates how you can use modular techniques to build better programs. A number of common modular programming patterns are covered, including divide-and-conquer, abstraction, encapsulation, wrappers and extensibility. You will also learn how to test your modules and packages, how to prepare your code for sharing with other people, and how to publish your modules and packages on GitHub and the Python Package Index so that other people can use them. Finally, you will learn how to use modular design techniques to be a more effective programmer.Style and approachThis book will be simple and straightforward, focusing on imparting learning through a wide array of examples that the readers can put into use as they read through the book. They should not only be able to understand the way modules help in improving development, but they should also be able to improvise on their techniques of writing concise and effective code.

Start building fast and robust applications with the power of Rust by your sideAbout This Book·Get started with the language to build scalable and high performance applications·This book will help C#/C++ developers gain better performance and memory management·Discover the power of Rust when developing concurrent applications for large and scalable softwareWho This Book Is ForThe book is for absolute beginners to Rust, who want to build high performance, concurrent applications for their projects. It is suitable for developers who have a basic knowledge of programming and developers who are using the C#/C++ language to write their applications. No knowledge of Rust is expected.What You Will Learn·Set up Rust for Windows, Linux, and OS X·Write effective code using Rust·Expand your Rust applications using libraries·Interface existing non-Rust libraries with your Rust applications·Use the standard library within your applications·Understand memory management within Rust and speed efficiency when passing variables·Create more complex data types·Study concurrency in Rust with multi-threaded applications and sync threading techniques to improve the performance of an application problemIn DetailRust is a highly concurrent and high performance language that focuses on safety and speed, memory management, and writing clean code. It also guarantees thread safety, and its aim is to improve the performance of existing applications. Its potential is shown by the fact that it has been backed by Mozilla to solve the critical problem of concurrency.Learning Rust will teach you to build concurrent, fast, and robust applications. From learning the basic syntax to writing complex functions, this book will is your one stop guide to get up to speed with the fundamentals of Rust programming. We will cover the essentials of the language, including variables, procedures, output, compiling, installing, and memory handling.You will learn how to write object-oriented code, work with generics, conduct pattern matching, and build macros. You will get to know how to communicate with users and other services, as well as getting to grips with generics, scoping, and more advanced conditions. You will also discover how to extend the compilation unit in Rust.By the end of this book, you will be able to create a complex application in Rust to move forward with.Style and approachThis comprehensive book will focus on the Rust syntax, functions, data types, and conducting pattern matching for programmers. It is divided into three parts and each part of the book has an objective to enable the readers to create their own applications at an appropriate level, ultimately towards creating complex applications.

Learn to build powerful and scalable applications with Flux, the architecture that serves billions of Facebook users every dayAbout This Book·This the first resource dedicated to the new architectural pattern that powers Facebook·You'll learn all the tips and tricks you need to get the most out of Flux·Filled with practical, hands-on samples, you'll not only understand how Flux works, but will be able to start building Flux-powered applications straight away·Written by Adam Boduch, software architect at Virtustream (EMC), and author of JavaScript at Scale, JavaScript Concurrency, and jQuery UI Cookbook for Packt PublishingWho This Book Is ForAre you trying to use React, but are struggling to get your head around Flux? Maybe you're tired of MV* spaghetti code at scale? Do you find yourself asking what the Flux?!Flux Architecture will guide you through everything you need to understand the Flux pattern, and design and build powerful web applications that rely on the Flux architecture.You don't need to know what Flux is or how it works to read along with the book. No knowledge of Flux's partner technology, ReactJS, is necessary to follow along, but it is recommended that you have a good working knowledge of JavaScript.What You Will Learn·Understand the Flux pattern and how it will impact your React applications·Build real-world applications that rely on Flux·Handle asynchronous actions in your application·Implement immutable stores with Immutable.js·Replace React.js with alternate View components such as jQuery and Handlebars·Test and benchmark your Flux architecture using Jest—Facebook's enhancement of the Jasmine libraryIn DetailWhilst React has become Facebook's poster-child for clean, complex, and modern web development, it has quietly been underpinned by its simplicity. It's just a view. The real beauty in React is actually the architectural pattern that handles data in and out of React applications: Flux. With Flux, you're able to build data-rich applications that engage your users, and scale to meet every demand. It is a key part of the Facebook technology stack that serves billions of users every day.This book will start by introducing the Flux pattern and help you get an understanding of what it is and how it works. After this, we'll build real-world React applications that highlight the power and simplicity of Flux in action. Finally, we look at the landscape of Flux and explore the Alt and Redux libraries that make React and Flux developments easier.Filled with fully-worked examples and code-first explanations, by the end of the book, you'll not only have a rock solid understanding of the architecture, but will be ready to implement Flux architecture in anger.Style and approachThis book is filled with practical, hands-on examples. You'll not only understand how Flux works, but will be able to start building Flux-powered applications straight away.

Design and implement efficient RESTful solutions with this practical hands-on guideAbout This Book·Create a fully featured RESTful API solution from scratch.·Learn how to leverage Node.JS, Express, MongoDB and NoSQL datastores to give an extra edge to your REST API design.·Use this practical guide to integrate MongoDB in your Node.js application.Who This Book Is ForThe ideal target audience for this book is web developers who have some experience with RESTful services. Familiarity with basic JavaScript programming techniques is required. No prior experience with Node.JS or Express.js is required.What You Will Learn·Install, develop, and test your own Node.js user modules·Comprehend the differences between an HTTP and a RESTful application·Optimize RESTful service URI routing with best practices·Eliminate third-party dependencies in your tests with mocking·Learn about NoSQL data stores and integrate MongoDB in your Node.js application with Mongoose·Secure your services with NoSQL database integration within Node.js applications·Enrich your development skills to create scalable, server-side, RESTful applications based on the Node.js platformIn DetailIn this era of cloud computing, every data provisioning solution is built in a scalable and fail-safe way. Thus, when building RESTful services, the right choice for the underlying platform is vital. Node.js, with its asynchronous, event-driven architecture, is exactly the right choice to build RESTful APIs.This book will help you enrich your development skills to create scalable, server-side, RESTful applications based on the Node.js platform.Starting with the fundamentals of REST, you will understand why RESTful web services are better data provisioning solution than other technologies. You will start setting up a development environment by installing Node.js, Express.js, and other modules. Next, you will write a simple HTTP request handler and create and test Node.js modules using automated tests and mock objects. You will then have to choose the most appropriate data storage type, having options between a key/value or document data store, and also you will implement automated tests for it. This module will evolve chapter by chapter until it turns into a full-fledged and secure Restful service.Style and approachCreate state of the art RESTful API solutions leveraging Node.JS 4.x.

A practical guide to rapidly and efficiently mastering Docker containers, along with tips and tricks learned in the field.About This Book·Use Docker containers, horizontal node scaling, modern orchestration tools (Docker Swarm, Kubernetes, and Mesos) and Continuous Integration/Continuous Delivery to manage your infrastructure.·Increase service density by turning often-idle machines into hosts for numerous Docker services.·Learn what it takes to build a true container infrastructure that is scalable, reliable, and resilient in the face of increased complexities from using container infrastructures.·Find out how to identify, debug, and mitigate most real-world, undocumented issues when deploying your own Docker infrastructure.·Learn tips and tricks of the trade from existing Docker infrastructures running in production environments.Who This Book Is ForThis book is aimed at system administrators, developers, DevOps engineers, and software engineers who want to get concrete, hands-on experience deploying multi-tier web applications and containerized microservices using Docker. This book is also for anyone who has worked on deploying services in some fashion and wants to take their small-scale setups to the next level (or simply to learn more about the process).What You Will Learn·Set up a working development environment and create a simple web service to demonstrate the basics·Learn how to make your service more usable by adding a database and an app server to process logic·Add resilience to your services by learning how to horizontally scale with a few containers on a single node·Master layering isolation and messaging to simplify and harden the connectivity between containers·Learn about numerous issues encountered at scale and their workarounds, from the kernel up to code versioning·Automate the most important parts of your infrastructure with continuous integrationIn DetailDeploying Docker into production is considered to be one of the major pain points in developing large-scale infrastructures, and the documentation available online leaves a lot to be desired. With this book, you will learn everything you wanted to know to effectively scale your deployments globally and build a resilient, scalable, and containerized cloud platform for your own use.The book starts by introducing you to the containerization ecosystem with some concrete and easy-to-digest examples; after that, you will delve into examples of launching multiple instances of the same container. From there, you will cover orchestration, multi-node setups, volumes, and almost every relevant component of this new approach to deploying services. Using intertwined approaches, the book will cover battle-tested tooling, or issues likely to be encountered in real-world scenarios, in detail. You will also learn about the other supporting components required for a true PaaS deployment and discover common options to tie the whole infrastructure together.At the end of the book, you learn to build a small, but functional, PaaS (to appreciate the power of the containerized service approach) and continue to explore real-world approaches to implementing even larger global-scale services.Style and approachThis in-depth learning guide shows you how to deploy your applications in production using Docker (from the basic steps to advanced concepts) and how to overcome challenges in Docker-based infrastructures. The book also covers practical use-cases in real-world examples, and provides tips and tricks on the various topics.

Mivel az informatika egyre inkább átsz?vi életünket, a szoftverek min?ségével kapcsolatos elvárások egyre magasabbak. Egy szoftver el?állítása azonban nem csak programozásból áll, és a programozóktól sem lehet elvárni emberfeletti képességeket, a megrendel? el nem mondott elképzelésének t?kéletesen megfelel?, teljesen hibamentes munkát, mivel csak az nem hibázik, aki nem is dolgozik. Az informatika világában a szoftvertesztel?k azok, akik a szoftverek min?ségéért dolgoznak. A szoftvertesztel?k?n óriási felel?sség nyugszik és folyamatosan elvárások kereszttüzében kell helytállniuk. Mégis, szoftvertesztelés nélkül a legt?bb szoftver el sem jutna a felhasználókig, vagy ha igen, akkor megjelenésük botrányokkal, valamint óriási anyagi és erk?lcsi veszteségekkel járna együtt, a rengeteg fel nem tárt programhiba miatt. Szoftvertesztelésre és tesztel?kre ezért mindenképp szükség van. K?nyvünk a professzionális szoftvertesztelés alapjaival ismerteti meg az olvasót, számos gyakorlati példával f?szerezve, mell?zve a száraz, pusztán technikai megk?zelítés? leírásokat, kezdve a szoftvertesztelés általános bemutatásától, a fogalmak ismertetését?l, majd részleteiben tárgyalva a szoftvertesztelést és annak helyét a fejlesztési folyamatokban. Segítségével jó adag gyakorlati ismerettel vértezhetjük fel magunkat, melynek során valódi, a tesztelést támogató alkalmazásokat ismerhetünk meg, biztos alapot nyújtva a szoftvertesztelésben elhelyezked? leend? és gyakorló szakembereknek a mindennapi munkájukhoz. A szoftverteszteléssel most ismerked? szakembereknek és laikusoknak kimondottan hasznos lehet ez a k?nyv, de fejleszt?k és cégvezet?k számára is tartogat hasznos információkat, melyek segítségével bevezethetik, illetve hatékonyabbá tehetik a szoftvertesztelést munkájuk során.

Ha kíváncsi az olyan témákra, mint például hogy miként lehet felt?rni egy jelszót, vagy egy webhelyet, esetleg hogyan lehet lehallgatni bárki kommunikációját egy nyílt wifi hálózaton, akkor ez a k?nyv ?nnek szól. Sokan azt hiszik, hogy ezek ?rd?ng?s dolgok, pedig egyáltalán nem azok. ?ppen ezért fontos, hogy védekezni is kell ellenük, ami szintén nem bonyolult, csak egy kis odafigyelésre van szükség. K?nyvünk mindkét oldalt megmutatja, elrettentésképpen a lehet?ségeket, okulásként a védekezési módokat. Ha ?n azt hiszi, hogy biztonságban van, hiszen nem csinál semmi illegálisat és még vírusirtó is van a gépén, akkor nagyon téved! Teljesk?r? védelem ugyanis nem létezik! Ha elolvassa ezt a k?nyvet, meg fog d?bbenni, hogy milyen sok támadási lehet?ség van adataink ellen. A k?nyv, azon túl, hogy ismerteti, mit jelentenek az információbiztonsági szakkifejezések olyan témákkal foglalkozik, mint hogy milyen eszk?z?k támadhatók és hogyan, hogyan dolgozik egy hacker, mekkora kockázatot jelent az emberi tényez? (social engineering), stb. Kitér a jelszavak biztonságára, a kül?nféle hackeléshez használható programok és azok kezelésére, a billenty?zetnaplózási lehet?ségekre, a hálózatok és weboldalak támadására és felt?résére, az online bankolási kockázatokra, a titkosítási módszerekre, illetve hogy mit érdemes tenni a biztonságos adattárolás érdekében.Természetesen senkit sem akarunk illegális tevékenységre buzdítani, célunk sokkal inkább azt megmutatni, hogy mekkora veszélynek vagyunk kitéve, ezáltal a támadási és védekezési lehet?ségek bemutatásával ?szt?n?zzük az embereket a biztonságosabb számítógéphasználatra.

Become a better web programmer by writing efficient and modular code using ES6 and ES8 About This Book ? Learn to write asynchronous code and improve the readability of your web applications ? Explore advanced concepts such as closures, Proxy, generators, Promise, async functions, and Atomics ? Use different design patterns to create structures to solve common organizational and processing issues Who This Book Is For If you’re a web developer with a basic understanding of JavaScript and wish to learn the latest features of ECMAScript for developing efficient web applications, this book is for you. What You Will Learn ? Organize JavaScript programs across multiple files, using ES modules ? Create and work with promises using the Promise object and methods ? Compose async functions to propagate and handle errors ? Solve organizational and processing issues with structures using design patterns ? Use classes to encapsulate and share behavior ? Orchestrate parallel programs using WebWorkers, SharedMemory, and Atomics ? Use and extend Map, Set, and Symbol to work with user-defined classes and simulate data types ? Explore new array methods to avoid looping with arrays and other collections In Detail ECMAScript Cookbook follows a modular approach with independent recipes covering different feature sets and specifications of ECMAScript to help you become an efficient programmer. This book starts off with organizing your JavaScript applications as well as delivering those applications to modem and legacy systems. You will get acquainted with features of ECMAScript 8 such as async, SharedArrayBuffers, and Atomic operations that enhance asynchronous and parallel operations. In addition to this, this book will introduce you to SharedArrayBuffers, which allow web workers to share data directly, and Atomic operations, which help coordinate behavior across the threads. You will also work with OOP and Collections, followed by new functions and methods on the built-in Object and Array types that make common operations more manageable and less error-prone. You will then see how to easily build more sophisticated and expressive program structures with classes and inheritance. In the end, we will cover Sets, Maps, and Symbols, which are the new types introduced in ECMAScript 6 to add new behaviors and allow you to create simple and powerful modules. By the end of the book, you will be able to produce more efficient, expressive, and simpler programs using the new features of ECMAScript. Style and approach This book will follow a modular approach covering independent recipes on different features of ECMAScript throughout the book.

Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow v1.7. About This Book ? Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow v1.7 ? Explore deep neural networks and layers of data abstraction with the help of this comprehensive guide ? Gain real-world contextualization through some deep learning problems concerning research and application Who This Book Is For The book is for people interested in machine learning and machine intelligence. A rudimentary level of programming in one language is assumed, as is a basic familiarity with computer science techniques and technologies, including a basic awareness of computer hardware and algorithms. Some competence in mathematics is needed to the level of elementary linear algebra and calculus. What You Will Learn ? Apply deep machine intelligence and GPU computing with TensorFlow v1.7 ? Access public datasets and use TensorFlow to load, process, and transform the data ? Discover how to use the high-level TensorFlow API to build more powerful applications ? Use deep learning for scalable object detection and mobile computing ? Train machines quickly to learn from data by exploring reinforcement learning techniques ? Explore active areas of deep learning research and applications In Detail Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks. This book is conceived for developers, data analysts, machine learning practitioners and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow v1.7, combined with other open source Python libraries. Throughout the book, you’ll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Factorization Machines. Discover how to attain deep learning programming on GPU in a distributed way. You'll come away with an in-depth knowledge of machine learning techniques and the skills to apply them to real-world projects. Style and approach This step-by-step guide explores common, and not so common, deep neural networks, and shows how they can be exploited in the real world with complex raw data. Benefit from practical examples, and learn how to implement different types of neural nets to build smart applications related to text, speech, and image data processing.

Learn the most powerful and primary programming language for writing smart contracts and find out how to write, deploy, and test smart contracts in Ethereum. About This Book ? Get you up and running with Solidity Programming language ? Build Ethereum Smart Contracts with Solidity as your scripting language ? Learn to test and deploy the smart contract to your private Blockchain Who This Book Is For This book is for anyone who would like to get started with Solidity Programming for developing an Ethereum smart contract. No prior knowledge of EVM is required. What You Will Learn ? Learn the basics and foundational concepts of Solidity and Ethereum ? Explore the Solidity language and its uniqueness in depth ? Create new accounts and submit transactions to blockchain ? Get to know the complete language in detail to write smart contracts ? Learn about major tools to develop and deploy smart contracts ? Write defensive code using exception handling and error checking ? Understand Truffle basics and the debugging process In Detail Solidity is a contract-oriented language whose syntax is highly influenced by JavaScript, and is designed to compile code for the Ethereum Virtual Machine. Solidity Programming Essentials will be your guide to understanding Solidity programming to build smart contracts for Ethereum and blockchain from ground-up. We begin with a brief run-through of blockchain, Ethereum, and their most important concepts or components. You will learn how to install all the necessary tools to write, test, and debug Solidity contracts on Ethereum. Then, you will explore the layout of a Solidity source file and work with the different data types. The next set of recipes will help you work with operators, control structures, and data structures while building your smart contracts. We take you through function calls, return types, function modifers, and recipes in object-oriented programming with Solidity. Learn all you can on event logging and exception handling, as well as testing and debugging smart contracts. By the end of this book, you will be able to write, deploy, and test smart contracts in Ethereum. This book will bring forth the essence of writing contracts using Solidity and also help you develop Solidity skills in no time. Style and approach Solidity is a high-level programming language best understood using examples. After covering basic concepts of Ethereum and Solidity, programming constructs will be explained with help of examples. As chapters progress, deployment, usage and testing of contacts will form major aspect of the book. Troubleshooting and unit testing is an important exercise and skill to master this language will also be covered in this book.

Building efficient Python applications at minimal cost by adopting serverless architectures About This Book ? Design and set up a data flow between cloud services and custom business logic ? Make your applications efficient and reliable using serverless architecture ? Build and deploy scalable serverless Python APIs Who This Book Is For This book is for Python developers who would like to learn about serverless architecture. Python programming knowledge is assumed. What You Will Learn ? Understand how AWS Lambda and Microsoft Azure Functions work and use them to create an application ? Explore various triggers and how to select them, based on the problem statement ? Build deployment packages for Lambda functions ? Master the finer details about building Lambda functions and versioning ? Log and monitor serverless applications ? Learn about security in AWS and Lambda functions ? Scale up serverless applications to handle huge workloads and serverless distributed systems in production ? Understand SAM model deployment in AWS Lambda In Detail Serverless architectures allow you to build and run applications and services without having to manage the infrastructure. Many companies have adopted this architecture to save cost and improve scalability. This book will help you design serverless architectures for your applications with AWS and Python. The book is divided into three modules. The first module explains the fundamentals of serverless architecture and how AWS lambda functions work. In the next module, you will learn to build, release, and deploy your application to production. You will also learn to log and test your application. In the third module, we will take you through advanced topics such as building a serverless API for your application. You will also learn to troubleshoot and monitor your app and master AWS lambda programming concepts with API references. Moving on, you will also learn how to scale up serverless applications and handle distributed serverless systems in production. By the end of the book, you will be equipped with the knowledge required to build scalable and cost-efficient Python applications with a serverless framework. Style and approach The book takes a pragmatic approach, using a real-world example to demonstrate building efficient, secure, and scalable serverless applications.

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.

Design and implement professional-level programs by leveraging modern data structures and algorithms in Rust Key Features * Improve your productivity by writing more simple and easy code in Rust * Discover the functional and reactive implementations of traditional data structures * Delve into new domains of Rust, including WebAssembly, networking, and command-line tools Book Description Rust is a powerful language with a rare combination of safety, speed, and zero-cost abstractions. This Learning Path is filled with clear and simple explanations of its features along with real-world examples, demonstrating how you can build robust, scalable, and reliable programs. You’ll get started with an introduction to Rust data structures, algorithms, and essential language constructs. Next, you will understand how to store data using linked lists, arrays, stacks, and queues. You’ll also learn to implement sorting and searching algorithms, such as Brute Force algorithms, Greedy algorithms, Dynamic Programming, and Backtracking. As you progress, you’ll pick up on using Rust for systems programming, network programming, and the web. You’ll then move on to discover a variety of techniques, right from writing memory-safe code, to building idiomatic Rust libraries, and even advanced macros. By the end of this Learning Path, you’ll be able to implement Rust for enterprise projects, writing better tests and documentation, designing for performance, and creating idiomatic Rust code. This Learning Path includes content from the following Packt products: * Mastering Rust - Second Edition by Rahul Sharma and Vesa Kaihlavirta * Hands-On Data Structures and Algorithms with Rust by Claus Matzinger What you will learn * Design and implement complex data structures in Rust * Create and use well-tested and reusable components with Rust * Understand the basics of multithreaded programming and advanced algorithm design * Explore application profiling based on benchmarking and testing * Study and apply best practices and strategies in error handling * Create efficient web applications with the Actix-web framework * Use Diesel for type-safe database interactions in your web application Who this book is for If you are already familiar with an imperative language and now want to progress from being a beginner to an intermediate-level Rust programmer, this Learning Path is for you. Developers who are already familiar with Rust and want to delve deeper into the essential data structures and algorithms in Rust will also find this Learning Path useful.

A comprehensive guide to programming with network sockets, implementing Internet protocols, designing IoT devices, and much more with C Key Features * Leverage your C or C++ programming skills to build powerful network applications * Get to grips with a variety of network protocols that allow you to load web pages, send emails, and do much more * Write portable network code for operating systems such as Windows, Linux, and macOS Book Description Network programming, a challenging topic in C, is made easy to understand with a careful exposition of socket programming APIs. This book gets you started with modern network programming in C and the right use of relevant operating system APIs. This book covers core concepts, such as hostname resolution with DNS, that are crucial to the functioning of the modern web. You’ll delve into the fundamental network protocols, TCP and UDP. Essential techniques for networking paradigms such as client-server and peer-to-peer models are explained with the help of practical examples. You’ll also study HTTP and HTTPS (the protocols responsible for web pages) from both the client and server perspective. To keep up with current trends, you’ll apply the concepts covered in this book to gain insights into web programming for IoT. You’ll even get to grips with network monitoring and implementing security best practices. By the end of this book, you’ll have experience of working with client-server applications, and be able to implement new network programs in C. The code in this book is compatible with the older C99 version as well as the latest C18 and C++17 standards. Special consideration is given to writing robust, reliable, and secure code that is portable across operating systems, including Winsock sockets for Windows and POSIX sockets for Linux and macOS. What you will learn * Uncover cross-platform socket programming APIs * Implement techniques for supporting IPv4 and IPv6 * Understand how TCP and UDP connections work over IP * Discover how hostname resolution and DNS work * Interface with web APIs using HTTP and HTTPS * Acquire hands-on experience with Simple Mail Transfer Protocol (SMTP) * Apply network programming to the Internet of Things (IoT) Who this book is for If you're a developer or a system administrator who wants to enter the world of network programming, this book is for you. Basic knowledge of C programming is assumed.

Learn dynamic programming with Julia to build apps for data analysis, visualization, machine learning, and the web Key Features * Leverage Julia's high speed and efficiency to build fast, efficient applications * Perform supervised and unsupervised machine learning and time series analysis * Tackle problems concurrently and in a distributed environment Book Description Julia offers the high productivity and ease of use of Python and R with the lightning-fast speed of C++. There’s never been a better time to learn this language, thanks to its large-scale adoption across a wide range of domains, including fintech, biotech and artificial intelligence (AI). You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. This Learning Path walks you through two important collection types: arrays and matrices. You’ll be taken through how type conversions and promotions work, and in further chapters you'll study how Julia interacts with operating systems and other languages. You’ll also learn about the use of macros, what makes Julia suitable for numerical and scientific computing, and how to run external programs. Once you have grasped the basics, this Learning Path goes on to how to analyze the Iris dataset using DataFrames. While building a web scraper and a web app, you’ll explore the use of functions, methods, and multiple dispatches. In the final chapters, you'll delve into machine learning, where you'll build a book recommender system. By the end of this Learning Path, you’ll be well versed with Julia and have the skills you need to leverage its high speed and efficiency for your applications. This Learning Path includes content from the following Packt products: * Julia 1.0 Programming - Second Edition by Ivo Balbaert * Julia Programming Projects by Adrian Salceanu What you will learn * Create your own types to extend the built-in type system * Visualize your data in Julia with plotting packages * Explore the use of built-in macros for testing and debugging * Integrate Julia with other languages such as C, Python, and MATLAB * Analyze and manipulate datasets using Julia and DataFrames * Develop and run a web app using Julia and the HTTP package * Build a recommendation system using supervised machine learning Who this book is for If you are a statistician or data scientist who wants a quick course in the Julia programming language while building big data applications, this Learning Path is for you. Basic knowledge of mathematics and programming is a must.

Teach your machine to think for itself! Key Features * Delve into supervised learning and grasp how a machine learns from data * Implement popular machine learning algorithms from scratch, developing a deep understanding along the way * Explore some of the most popular scientific and mathematical libraries in the Python language Book Description Supervised machine learning is used in a wide range of sectors (such as finance, online advertising, and analytics) because it allows you to train your system to make pricing predictions, campaign adjustments, customer recommendations, and much more while the system self-adjusts and makes decisions on its own. As a result, it's crucial to know how a machine “learns” under the hood. This book will guide you through the implementation and nuances of many popular supervised machine learning algorithms while facilitating a deep understanding along the way. You’ll embark on this journey with a quick overview and see how supervised machine learning differs from unsupervised learning. Next, we explore parametric models such as linear and logistic regression, non-parametric methods such as decision trees, and various clustering techniques to facilitate decision-making and predictions. As we proceed, you'll work hands-on with recommender systems, which are widely used by online companies to increase user interaction and enrich shopping potential. Finally, you’ll wrap up with a brief foray into neural networks and transfer learning. By the end of this book, you’ll be equipped with hands-on techniques and will have gained the practical know-how you need to quickly and powerfully apply algorithms to new problems. What you will learn * Crack how a machine learns a concept and generalize its understanding to new data * Uncover the fundamental differences between parametric and non-parametric models * Implement and grok several well-known supervised learning algorithms from scratch * Work with models in domains such as ecommerce and marketing * Expand your expertise and use various algorithms such as regression, decision trees, and clustering * Build your own models capable of making predictions * Delve into the most popular approaches in deep learning such as transfer learning and neural networks Who this book is for This book is for aspiring machine learning developers who want to get started with supervised learning. Intermediate knowledge of Python programming—and some fundamental knowledge of supervised learning—are expected.

A comprehensive guide to get started with Java and gain insights into major concepts such as object-oriented, functional, and reactive programming Key Features * Strengthen your knowledge of important programming concepts and the latest features in Java * Explore core programming topics including GUI programming, concurrency, and error handling * Learn the idioms and best practices for writing high-quality Java code Book Description Java is one of the preferred languages among developers, used in everything right from smartphones, and game consoles to even supercomputers, and its new features simply add to the richness of the language. This book on Java programming begins by helping you learn how to install the Java Development Kit. You will then focus on understanding object-oriented programming (OOP), with exclusive insights into concepts like abstraction, encapsulation, inheritance, and polymorphism, which will help you when programming for real-world apps. Next, you’ll cover fundamental programming structures of Java such as data structures and algorithms that will serve as the building blocks for your apps. You will also delve into core programming topics that will assist you with error handling, debugging, and testing your apps. As you progress, you’ll move on to advanced topics such as Java libraries, database management, and network programming, which will hone your skills in building professional-grade apps. Further on, you’ll understand how to create a graphic user interface using JavaFX and learn to build scalable apps by taking advantage of reactive and functional programming. By the end of this book, you’ll not only be well versed with Java 10, 11, and 12, but also gain a perspective into the future of this language and software development in general. What you will learn * Learn and apply object-oriented principles * Gain insights into data structures and understand how they are used in Java * Explore multithreaded, asynchronous, functional, and reactive programming * Add a user-friendly graphic interface to your application * Find out what streams are and how they can help in data processing * Discover the importance of microservices and use them to make your apps robust and scalable * Explore Java design patterns and best practices to solve everyday problems * Learn techniques and idioms for writing high-quality Java code Who this book is for Students, software developers, or anyone looking to learn new skills or even a language will find this book useful. Although this book is for beginners, professional programmers can benefit from it too. Previous knowledge of Java or any programming language is not required.

Supervised and unsupervised machine learning made easy in Scala with this quick-start guide. Key Features * Construct and deploy machine learning systems that learn from your data and give accurate predictions * Unleash the power of Spark ML along with popular machine learning algorithms to solve complex tasks in Scala. * Solve hands-on problems by combining popular neural network architectures such as LSTM and CNN using Scala with DeepLearning4j library Book Description Scala is a highly scalable integration of object-oriented nature and functional programming concepts that make it easy to build scalable and complex big data applications. This book is a handy guide for machine learning developers and data scientists who want to develop and train effective machine learning models in Scala. The book starts with an introduction to machine learning, while covering deep learning and machine learning basics. It then explains how to use Scala-based ML libraries to solve classification and regression problems using linear regression, generalized linear regression, logistic regression, support vector machine, and Na?ve Bayes algorithms. It also covers tree-based ensemble techniques for solving both classification and regression problems. Moving ahead, it covers unsupervised learning techniques, such as dimensionality reduction, clustering, and recommender systems. Finally, it provides a brief overview of deep learning using a real-life example in Scala. What you will learn * Get acquainted with JVM-based machine learning libraries for Scala such as Spark ML and Deeplearning4j * Learn RDDs, DataFrame, and Spark SQL for analyzing structured and unstructured data * Understand supervised and unsupervised learning techniques with best practices and pitfalls * Learn classification and regression analysis with linear regression, logistic regression, Na?ve Bayes, support vector machine, and tree-based ensemble techniques * Learn effective ways of clustering analysis with dimensionality reduction techniques * Learn recommender systems with collaborative filtering approach * Delve into deep learning and neural network architectures Who this book is for This book is for machine learning developers looking to train machine learning models in Scala without spending too much time and effort. Some fundamental knowledge of Scala programming and some basics of statistics and linear algebra is all you need to get started with this book.

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.