If you are interested in quantitative finance, financial modeling, and trading, or simply want to learn how Python and pandas can be applied to finance, then this book is ideal for you. Some knowledge of Python and pandas is assumed. Interest in financial concepts is helpful, but no prior knowledge is expected.

This book is intended for Python programmers interested in learning how to do natural language processing. Maybe you’ve learned the limits of regular expressions the hard way, or you’ve realized that human language cannot be deterministically parsed like a computer language. Perhaps you have more text than you know what to do with, and need automated ways to analyze and structure that text. This Cookbook will show you how to train and use statistical language models to process text in ways that are practically impossible with standard programming tools. A basic knowledge of Python and the basic text processing concepts is expected. Some experience with regular expressions will also be helpful.

The book requires no prior knowledge of JavaScript and works from the ground up to give you a thorough grounding in this powerful language. If you do already know some JavaScript, you will find plenty of eye-openers as you discover just what the language can do. This book takes a do-it-yourself approach when it comes to writing code, because the best way to really learn a programming language is by writing code. You are encouraged to type code into Firebug's console, see how it works and then tweak it and play around with it. There are practice questions at the end of each chapter to help review what you have learned.

This book follows a standard tutorial approach with approximately 750 code samples spread through the 19 chapters. This amounts to over 5,900 lines of code that illustrate each concept. This book is aimed at programmers who have already learned the basics of objectoriented Python and need to write more sophisticated, flexible code that integrates seamlessly with the rest of Python. This book assumes a computer science background, with experience of common Python design patterns.

Over 140 practical recipes to help you make sense of your data with ease and build production-ready data apps About This Book Analyze Big Data sets, create attractive visualizations, and manipulate and process various data types Packed with rich recipes to help you learn and explore amazing algorithms for statistics and machine learning Authored by Ivan Idris, expert in python programming and proud author of eight highly reviewed books Who This Book Is For This book teaches Python data analysis at an intermediate level with the goal of transforming you from journeyman to master. Basic Python and data analysis skills and affinity are assumed. What You Will Learn Set up reproducible data analysis Clean and transform data Apply advanced statistical analysis Create attractive data visualizations Web scrape and work with databases, Hadoop, and Spark Analyze images and time series data Mine text and analyze social networks Use machine learning and evaluate the results Take advantage of parallelism and concurrency In Detail Data analysis is a rapidly evolving field and Python is a multi-paradigm programming language suitable for object-oriented application development and functional design patterns. As Python offers a range of tools and libraries for all purposes, it has slowly evolved as the primary language for data science, including topics on: data analysis, visualization, and machine learning. Python Data Analysis Cookbook focuses on reproducibility and creating production-ready systems. You will start with recipes that set the foundation for data analysis with libraries such as matplotlib, NumPy, and pandas. You will learn to create visualizations by choosing color maps and palettes then dive into statistical data analysis using distribution algorithms and correlations. You’ll then help you find your way around different data and numerical problems, get to grips with Spark and HDFS, and then set up migration *s for web mining. In this book, you will dive deeper into recipes on spectral analysis, smoothing, and bootstrapping methods. Moving on, you will learn to rank stocks and check market efficiency, then work with metrics and clusters. You will achieve parallelism to improve system performance by using multiple threads and speeding up your code. By the end of the book, you will be capable of handling various data analysis techniques in Python and devising solutions for problem scenarios. Style and Approach The book is written in “cookbook” style striving for high realism in data analysis. Through the recipe-based format, you can read each recipe separately as required and immediately apply the knowledge gained.

Learn how to build physical computing systems using BeagleBone Black and Python About This Book Get to grips with the fundamentals of BeagleBone Leverage Python *s to program BeagleBone for your requirements Build four exciting projects, from home automation to a tele-controlled robot Who This Book Is For This book is intended for hobbyists and consumers who wish to create impressive projects using BeagleBone. You must be familiar with Python programming. What You Will Learn Program on BeagleBone Black using Python Interface sensors and actuators to BeagleBone Black Build your own real-time physical computing systems Connect physical computing systems to cloud servers Build your own home automation and home security system Build your own tele-controlled robot with real-time video streaming In Detail BeagleBone is a low cost, community-supported development platform to develop a variety of electronic projects. This book will introduce you to BeagleBone and get you building fun, cool, and innovative projects with it. Start with the specifications of BeagleBone Black and its operating systems, then get to grips with the GPIOs available in BeagleBone Black. Work through four types of exciting projects: building real-time physical computing systems, home automation, image processing for a security system, and building your own tele-controlled robot and learn the fundamentals of a variety of projects in a single book. By the end of this book, you will be able to write code for BeagleBone in order to operate hardware and impart decision-making capabilities with the help of efficient coding in Python. Style and approach This book is a step by step guide that will walk you through the fundamentals of building different projects using BeagleBone Black.

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.

Design and implement scalable and maintainable RESTful solutions with Node.js 10 About This Book ? Create rich and scalable RESTful API solutions from scratch ? Explore the new features of Node.js 10, Express 4.0, and MongoDB ? Integrate MongoDB in your Node.js application to store and secure your data Who This Book Is For If you are a web developer keen to enrich your development skills to create server-side RESTful applications based on the Node.js platform, this book is for you. Some knowledge of REST would be an added advantage, but is definitely not a necessity. What You Will Learn ? Install, develop, and test your own Node.js user modules ? Understand the differences between HTTP and RESTful applications ? Use self-descriptive URLs and set accurate HTTP status codes ? Eliminate third-party dependencies in your tests with mocking ? Implement automation tests for a REST-enabled endpoint with Mocha ? Secure your services with NoSQL database integration within Node.js applications ? Integrate a simple frontend using JavaScript libraries available on a CDN server In Detail When building RESTful services, it is really important to choose the right framework. Node.js, with its asynchronous, event-driven architecture, is exactly the right choice for building RESTful APIs. This third edition of RESTful Web API Design with Node.js 10 will teach you to create scalable and rich RESTful applications based on the Node.js platform. You will be introduced to the latest NPM package handler and understand how to use it to customize your RESTful development process. You will begin by understanding the key principle that makes an HTTP application a RESTful-enabled application. After writing a simple HTTP request handler, you will create and test Node.js modules using automated tests and mock objects; explore using the NoSQL database, MongoDB, to store data; and get to grips with using self-descriptive URLs. You’ll learn to set accurate HTTP status codes along with understanding how to keep your applications backward-compatible. Also, while implementing a full-fledged RESTful service, you will use Swagger to document the API and implement automation tests for a REST-enabled endpoint with Mocha. Lastly, you will explore some authentication techniques to secure your application. Style and approach Step-by-step practical guide to building RESTful applications

Design clever algorithms that can uncover interesting structures and hidden relationships in unstructured, unlabeled data Key Features * Learn how to select the most suitable Python library to solve your problem * Compare k-Nearest Neighbor (k-NN) and non-parametric methods and decide when to use them * Delve into the applications of neural networks using real-world datasets Book Description Unsupervised learning is a useful and practical solution in situations where labeled data is not available. Applied Unsupervised Learning with Python guides you on the best practices for using unsupervised learning techniques in tandem with Python libraries and extracting meaningful information from unstructured data. The course begins by explaining how basic clustering works to find similar data points in a set. Once you are well versed with the k-means algorithm and how it operates, you’ll learn what dimensionality reduction is and where to apply it. As you progress, you’ll learn various neural network techniques and how they can improve your model. While studying the applications of unsupervised learning, you will also understand how to mine topics that are trending on Twitter and Facebook and build a news recommendation engine for users. You will complete the course by challenging yourself through various interesting activities such as performing a Market Basket Analysis and identifying relationships between different merchandises. By the end of this course, you will have the skills you need to confidently build your own models using Python. What you will learn * Understand the basics and importance of clustering * Build k-means, hierarchical, and DBSCAN clustering algorithms from scratch with built-in packages * Explore dimensionality reduction and its applications * Use scikit-learn (sklearn) to implement and analyse principal component analysis (PCA)on the Iris dataset * Employ Keras to build autoencoder models for the CIFAR-10 dataset * Apply the Apriori algorithm with machine learning extensions (Mlxtend) to study transaction data Who this book is for This course is designed for developers, data scientists, and machine learning enthusiasts who are interested in unsupervised learning. Some familiarity with Python programming along with basic knowledge of mathematical concepts including exponents, square roots, means, and medians will be beneficial.

This book is aimed at system administrators and technical architects moving from a virtualized environment to cloud environments; who are familiar with cloud computing platforms. Knowledge of virtualization and managing Linux environments is expected. Prior knowledge or experience of OpenStack is not required, although beneficial.

This book is intended for software developers who want to use parallel programming techniques to write powerful and efficient code. After reading this book, you will be able to master the basics and the advanced features of parallel computing. The Python programming language is easy to use and allows nonexperts to deal with and easily understand the topics exposed in this book.

Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. A concise guide full of step-by-step recipes to teach you how to install and configure a Debian web server.This is an ideal book if you are an administrator on a Development Operations team or infrastructure management, who is passionate about Linux and their Web applications but have no previous experience with Debian or APT-based systems.

A step-by-step guide, packed with examples of practical numerical analysis that will give you a comprehensive, but concise overview of NumPy. This book is for programmers, scientists, or engineers, who have basic Python knowledge and would like to be able to do numerical computations with Python.

This book is suitable for the novice and experienced system administrators, programmers, and anyone who would like to learn how to work with the TCP/IP protocol suite. It can be read even by those who have little background in networking

Web penetration testing by becoming an ethical hacker. Protect the web by learning the tools, and the tricks of the web application attacker. Key Features * Builds on books and courses on penetration testing for beginners * Covers both attack and defense perspectives * Examines which tool to deploy to suit different applications and situations Book Description Becoming the Hacker will teach you how to approach web penetration testing with an attacker's mindset. While testing web applications for performance is common, the ever-changing threat landscape makes security testing much more difficult for the defender. There are many web application tools that claim to provide a complete survey and defense against potential threats, but they must be analyzed in line with the security needs of each web application or service. We must understand how an attacker approaches a web application and the implications of breaching its defenses. Through the first part of the book, Adrian Pruteanu walks you through commonly encountered vulnerabilities and how to take advantage of them to achieve your goal. The latter part of the book shifts gears and puts the newly learned techniques into practice, going over scenarios where the target may be a popular content management system or a containerized application and its network. Becoming the Hacker is a clear guide to web application security from an attacker's point of view, from which both sides can benefit. What you will learn * Study the mindset of an attacker * Adopt defensive strategies * Classify and plan for standard web application security threats * Prepare to combat standard system security problems * Defend WordPress and mobile applications * Use security tools and plan for defense against remote execution Who this book is for The reader should have basic security experience, for example, through running a network or encountering security issues during application development. Formal education in security is useful, but not required. This title is suitable for people with at least two years of experience in development, network management, or DevOps, or with an established interest in security.

Introduction to deep learning and PyTorch by building a convolutional neural network and recurrent neural network for real-world use cases such as image classification, transfer learning, and natural language processing. Key Features *Clear and concise explanations *Gives important insights into deep learning models *Practical demonstration of key concepts Book Description PyTorch is extremely powerful and yet easy to learn. It provides advanced features, such as supporting multiprocessor, distributed, and parallel computation. This book is an excellent entry point for those wanting to explore deep learning with PyTorch to harness its power. This book will introduce you to the PyTorch deep learning library and teach you how to train deep learning models without any hassle. We will set up the deep learning environment using PyTorch, and then train and deploy different types of deep learning models, such as CNN, RNN, and autoencoders. You will learn how to optimize models by tuning hyperparameters and how to use PyTorch in multiprocessor and distributed environments. We will discuss long short-term memory network (LSTMs) and build a language model to predict text. By the end of this book, you will be familiar with PyTorch's capabilities and be able to utilize the library to train your neural networks with relative ease. What you will learn *Set up the deep learning environment using the PyTorch library *Learn to build a deep learning model for image classification *Use a convolutional neural network for transfer learning *Understand to use PyTorch for natural language processing *Use a recurrent neural network to classify text *Understand how to optimize PyTorch in multiprocessor and distributed environments *Train, optimize, and deploy your neural networks for maximum accuracy and performance *Learn to deploy production-ready models Who this book is for Developers and Data Scientist familiar with Machine Learning but new to deep learning, or existing practitioners of deep learning who would like to use PyTorch to train their deep learning models will find this book to be useful. Having knowledge of Python programming will be an added advantage, while previous exposure to PyTorch is not needed.

This is the book for you if you are a student, hobbyist, developer, or designer with little or no programming and hardware prototyping experience, and you want to develop IoT applications. If you are a software developer or a hardware designer and want to create connected devices applications, then this book will help you get started.

If you are a frontend developer with considerable knowledge of jQuery UI and want to take this expertise to the next level, then this book is for you.

If you are a PHP programmer or developer looking for a framework to quickly develop your applications, this book is for you. The prerequisites needed would be prior experience with CodeIgniter.

If you are a C# developer who wants to learn a new way of querying data and utilizing it in applications efficiently for data binding or other operations, then this book is for you. Basic knowledge of ADO.NET is assumed.

If you are a system administrator who has some experience with virtualization and already uses VMware vCenter, but wishes to learn more, then this is the book for you. If you are looking for tips or shortcuts for common administration tasks as well as workarounds for pain points in vSphere administration, you'll find this guide useful.