Thoughtful Machine Learning with Python: A Test-Driven Approach

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Gain the confidence you need to apply machine learning in your daily work. With this practical guide, author Matthew Kirk shows you how to integrate and test machine learning algorithms in your code, without the academic subtext.Featuring graphs and highlighted code examples throughout, the book features tests with Python’s Numpy, Pandas, Scikit-Learn, and SciPy data science libraries. If you’re a software engineer or business analyst interested in data science, this book will help you:Reference real-world examples to test each algorithm through engaging, hands-on exercisesApply test-driven development (TDD) to write and run tests before you start codingExplore techniques for improving your machine-learning models with data extraction and feature developmentWatch out for the risks of machine learning, such as underfitting or overfitting dataWork with K-Nearest Neighbors, neural networks, clustering, and other algorithms

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Bash Pocket Reference: Help for Power Users and Sys Admins

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It’s simple: if you want to interact deeply with Mac OS X, Linux, and other Unix-like systems, you need to know how to work with the Bash shell. This concise little book puts all of the essential information about Bash right at your fingertips.You’ll quickly find answers to the annoying questions that generally come up when you’re writing shell scripts: What characters do you need to quote? How do you get variable substitution to do exactly what you want? How do you use arrays? Updated for Bash version 4.4, this book has the answers to these and other problems in a format that makes browsing quick and easy.Topics include:Invoking the shellSyntaxFunctions and variablesArithmetic expressionsCommand historyProgrammable completionJob controlShell optionsCommand executionCoprocessesRestricted shellsBuilt-in commands

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Camel in Action

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Apache Camel is a Java framework that lets you implement the standard enterprise integration patterns in a few lines of code. With a concise but sophisticated DSL you snap integration logic into your app, Lego-style, using Java, XML, or Scala. Camel supports over 80 common transports such as HTTP,REST, JMS, and Web Services.Camel in Action is a Camel tutorial full of small examples showing how to work with the integration patterns. It starts with core concepts like sending, receiving, routing, and transforming data.It then shows you the entire lifecycle and goes in depth on how to test, deal with errors, scale, deploy, and even monitor your app- details you can find only in the Camel code itself. Written by the developers of Camel, this book distills their experience and practical insights so that you can tackle integration tasks like a pro.Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.What's

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Violent Python: A Cookbook for Hackers, Forensic Analysts, Penetration Testers and Security Engineers

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Violent Python shows you how to move from a theoretical understanding of offensive computing concepts to a practical implementation. Instead of relying on another attacker’s tools, this book will teach you to forge your own weapons using the Python programming language. This book demonstrates how to write Python scripts to automate large-scale network attacks, extract metadata, and investigate forensic artifacts. It also shows how to write code to intercept and analyze network traffic using Python, craft and spoof wireless frames to attack wireless and Bluetooth devices, and how to data-mine popular social media websites and evade modern anti-virus. Demonstrates how to write Python scripts to automate large-scale network attacks, extract metadata, and investigate forensic artifactsWrite code to intercept and analyze network traffic using Python. Craft and spoof wireless frames to attack wireless and Bluetooth devicesData-mine popular social media websites and evade modern anti-virus

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Architecting for Scale: High Availability for Your Growing Applications

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Every day, companies struggle to scale critical applications. As traffic volume and data demands increase, these applications become more complicated and brittle, exposing risks and compromising availability. This practical guide shows IT, devops, and system reliability managers how to prevent an application from becoming slow, inconsistent, or downright unavailable as it grows.Scaling isn’t just about handling more users; it’s also about managing risk and ensuring availability. Author Lee Atchison provides basic techniques for building applications that can handle huge quantities of traffic, data, and demand without affecting the quality your customers expect.In five parts, this book explores:Availability: learn techniques for building highly available applications, and for tracking and improving availability going forwardRisk management: identify, mitigate, and manage risks in your application, test your recovery/disaster plans, and build out systems that contain fewer risksServi

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Python Pocket Reference: Python In Your Pocket (Pocket Reference (O'Reilly))

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Updated for both Python 3.4 and 2.7, this convenient pocket guide is the perfect on-the-job quick reference. You’ll find concise, need-to-know information on Python types and statements, special method names, built-in functions and exceptions, commonly used standard library modules, and other prominent Python tools. The handy index lets you pinpoint exactly what you need.Written by Mark Lutz—widely recognized as the world’s leading Python trainer—Python Pocket Reference is an ideal companion to O’Reilly’s classic Python tutorials, Learning Python and Programming Python, also written by Mark.This fifth edition covers:Built-in object types, including numbers, lists, dictionaries, and moreStatements and syntax for creating and processing objectsFunctions and modules for structuring and reusing codePython’s object-oriented programming toolsBuilt-in functions, exceptions, and attributesSpecial operator overloading methodsWidely used standard library modules and extensionsComma

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Microsoft ASP.NET Fast & Easy Web Development

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Don't spend your time wading through manuals to learn ASP.NET. Spend it doing what you do best--creating Web pages! Begin with an introduction to the .NET initiative, and then work your way through the concepts of ASP.NET, Visual Basic.NET, and ADO.NET. Combining easy-to-understand instructions with visual examples, this book offers a unique, hands-on approach to ASP.NET..

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The Biblical Basis of Christian Counseling for People Helpers: Relating the Basic Teachings of Scripture to People's Problems

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Professional JavaScript for Web Developers

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This book provides a developer-level introduction along with more advanced and useful features of JavaScript. Coverage includes: JavaScript use with HTML to create dynamic webpages, language concepts including syntax and flow control statements variable handling given their loosely typed nature built-in reference types such as object and array object-oriented programing powerful aspects of function expressions Browser Object Model allowing interaction with the browser itself detecting the client and its capabilities Document Object Model (DOM) objects available in DOM Level 1 how DOM Levels 2 and 3 augmented the DOM events, legacy support, and how the DOM redefined how events should work enhancing form interactions and working around browser limitations using the tag to create on-the-fly graphics JavaScript API changes in HTML5 how browsers handle JavaScript errors and error handling features of JavaScript used to read and manipulate XML data the JSON data format as an alternative to

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Python Data Science Handbook: Essential Tools for Working with Data

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For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you’ll learn how to use:IPython and Jupyter: provide computational environments for data scientists using PythonNumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in PythonPandas: features

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