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Python for Probability, Statistics, and Machine Learning 英文原版。内含pdf和epub两种格式。

Practical Data Science Cookbook - Second Edition是真正原版英文pdf。

python数据挖掘由机械工业出版社翻译出版，英文为：Mastering Data Mining with Python。内附中文扫描清晰版和英文原版pdf/epub。

Python数据可视化 机械工业出版社翻译出版。英文为Mastering Python Data Visualization。内附中文清晰扫描版和英文原版pdf。

Pandas Cookbook Copyright © 2017 Packt Publishing Chapter 1, Pandas Foundations, covers the anatomy and vocabulary used to identify the components of the two main pandas data structures, the Series and the DataFrame. Each column must have exactly one type of data, and each of these data types is covered. You will learn how to unleash the power of the Series and the DataFrame by calling and chaining together their methods. Chapter 2, Essential DataFrame Operations, focuses on the most crucial and common operations that you will perform during data analysis. Chapter 3, Beginning Data Analysis, helps you develop a routine to get started after reading in your data. Other interesting discoveries will be made. Chapter 4, Selecting Subsets of Data, covers the many varied and potentially confusing ways of selecting different subsets of data. Chapter 5, Boolean Indexing, covers the process of querying your data to select subsets of it based on Boolean conditions. Chapter 6, Index Alignment, targets the very important and often misunderstood index object. Misuse of the Index is responsible for lots of erroneous results, and these recipes show you how to use it correctly to deliver powerful results. Chapter 7, Grouping for Aggregation, Filtration, and Transformation, covers the powerful grouping capabilities that are almost always necessary during a data analysis. You will build customized functions to apply to your groups. Chapter 8, Restructuring Data into Tidy Form, explains what tidy data is and why it’s so important, and then it shows you how to transform many different forms of messy datasets into tidy ones. Chapter 9, Combining Pandas Objects, covers the many available methods tocombine DataFrames and Series vertically or horizontally. We will also do some web-scraping to compare President Trump's and Obama's approval rating and connect to an SQL relational database. Chapter 10, Time Series Analysis, covers advanced and powerful time series capabilities to dissect by any dimension of time possible. Chapter 11, Visualization with Matplotlib, Pandas, and Seaborn, introduces the matplotlib library, which is responsible for all of the plotting in pandas. We will then shift focus to the pandas plot method and, finally, to the seaborn library, which is capable of producing aesthetically pleasing visualizations not directly available in pandas

Author: Wes McKinney ISBN-10: 1491957662 Year: 2017 Pages: 544 Language: English File format: PDF Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples

Python GUI Programming Cookbook Second Edition Copyright © 2017 Packt Publishing All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews. Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book. Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals.However, Packt Publishing cannot guarantee the accuracy of this information.

Learning TensorFlow by Tom Hope, Yehezkel S. Resheff, and Itay Lieder Copyright © 2017 Tom Hope, Itay Lieder, and Yehezkel S. Resheff. All rights reserved. Printed in the United States of America. Published by O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472. O’Reilly books may be purchased for educational, business, or sales promotional use. Online editions are also available for most titles (http://oreilly.com/safari). For more information, contact our corporate/insti‐ tutional sales department: 800-998-9938 or [email protected]

Author: Matthew Kirk ISBN-10: 1491924136 Year: 2017 Pages: 216 Language: English File size: 8.6 MB File format:PDF Category: Data Mining Book Description: 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 exercises Apply test-driven development (TDD) to write and run tests before you start coding Explore techniques for improving your machine-learning models with data extraction and feature development Watch out for the risks of machine learning, such as underfitting or overfitting data Work with K-Nearest Neighbors, neural networks, clustering, and other algorithms

Interactive Applications Using Matplotlib Copyright © 2015 Packt Publishing What this book covers Chapter 1, Introducing Interactive Plotting, covers basic figure-axes-artist hierarchy and other Matplotlib essentials such as displaying the plot. It also introduces you to theinteractive Matplotlib figure. Chapter 2, Using Events and Callbacks, provides Matplotlib's events and a callback system to bring your figures to life. It also explains how you can extend it with custom events, making the application truly interactive. Chapter 3, Animations, deals with ArtistAnimation, FuncAnimation, and timers to make animations of all types. It also deals with animations that can be saved as movies. Chapter 4, Widgets, covers built-in widgets such as buttons, checkboxes, selectors,lassos, and sliders, which are all explained and demonstrated. Here, you'll also learn about other useful third-party widgets and tools. Chapter 5, Embedding Matplotlib, teaches you how to add GUI elements to an existing Matplotlib application. Here you'll also see how to add your interactive Matplotlib figure to an existing GUI application. Identical examples are presented using GTK, Tkinter, wxWidgets, and Qt.

English | 2016 | ISBN: 1785280694 | 156 Pages | True PDF | 9 MB Pen test your system like a pro and overcome vulnerabilities by leveraging Python scripts, libraries, and tools. Penetration testing is a practice of testing a computer system, network, or web application to find weaknesses in security that an attacker can exploit. Effective Python Penetration Testing will help you utilize your Python scripting skills to safeguard your networks from cyberattacks. We will begin by providing you with an overview of Python scripting and penetration testing. You will learn to analyze network traffic by writing Scapy scripts and will see how to fingerprint web applications with Python libraries such as ProxMon and Spynner. Moving on, you will find out how to write basic attack scripts, and will develop debugging and reverse engineering skills with Python libraries. Toward the end of the book, you will discover how to utilize cryptography toolkits in Python and how to automate Python tools and libraries. What you will learn: - Write Scapy scripts to investigate network traffic - Get to know application fingerprinting techniques with Python - Understand the attack scripting techniques - Write fuzzing tools with pentesting requirements - Learn basic attack scripting methods - Utilize cryptographic toolkits in Python - Automate pentesting with Python tools and libraries

ython is one of the most popular programming languages of our era; the Python Requests library is one of the world’s best clients, with the highest number of downloads. It allows hassle-free interactions with web applications using simple procedures. You will be shown how to mock HTTP Requests using HTTPretty, and will learn to interact with social media using Requests. This book will help you to grasp the art of web scraping with the BeautifulSoup and Python Requests libraries, and will then paddle you through Requests impressive ability to interact with APIs. It will empower you with the best practices for seamlessly drawing data from web apps. Last but not least, you will get the chance to polish your skills by implementing a RESTful Web API with Python and Flask! Who This Book Is For If you are a Python administrator or developer interested in interacting with web APIs and have a passion for creating your own web applications, this is the book for you. Basic knowledge of Python programming, APIs, and web services will be an advantage. What You Will Learn Demonstrate the use of Python Requests with the help of examples Use the Requests module to deal with the inner sections of the request-response cycles Implement the RESTful Web API with Python Requests Authenticate Requests using different authentication methods Emulate server actions and interact with a mock server Interact with social networking sites such as Facebook, Twitter, and reddit Scrape the Web with Python Requests and BeautifulSoup Build your own web application with Flask

C#作为微软的旗舰编程语言，深受程序员喜爱，是编写高效应用程序的shouxuan语言。VisualC#2015提供了大量新功能，本书围绕语言的基础知识和这些新功能全面介绍了如何利用VisualStudio2015和.NETFramework4.6编写C#应用程序。本书沿袭深受读者欢迎的StepbyStep风格，通过合理的练习引导读者逐步构建在Windows10上运行的应用程序、访问SQLServer数据库以及开发多线程应用等。 全书共27章，结构清晰，叙述清楚。所有练习均在VisualStudio2015简体中文版上进行过全面演练。无论是刚开始接触面向对象编程的新手，还是打算迁移到C#的C、C++或Java程序员，都可以从本书汲取到新的知识。迅速掌握C#编程技术。 目录 第I部分VisualC#和VisualStudio2015概述 第1章欢迎进入C#编程世界3 第2章使用变量、操作符和表达式27 第3章方法和作用域48 第4章使用判断语句72 第5章使用复合赋值和循环语句89 第6章管理错误和异常105 第II部分理解C#对象模型 第7章创建并管理类和对象127 第8章理解值和引用146 第9章使用枚举和结构创建值类型167 第10章使用数组185 第11章理解参数数组204 第12章使用继承215 第13章创建接口和定义抽象类236 第14章使用垃圾回收和资源管理260 第III部分用C#定义可扩展类型 第15章实现属性以访问字段281 第16章使用索引器302 第17章泛型概述317 第18章使用集合344 第19章枚举集合366 第20章分离应用程序逻辑并处理事件379 第21章使用查询表达式来查询内存中的数据406 第22章操作符重载428 第IV部分用C#构建UWP应用 第23章使用任务提高吞吐量451 第24章通过异步操作提高响应速度489 第25章实现UWP应用的用户界面525 第26章在UWP应用中显示和搜索数据567 第27章在UWP应用中访问远程数据库608

C#作为微软的旗舰编程语言，深受程序员喜爱，是编写高效应用程序的shouxuan语言。VisualC#2015提供了大量新功能，本书围绕语言的基础知识和这些新功能全面介绍了如何利用VisualStudio2015和.NETFramework4.6编写C#应用程序。本书沿袭深受读者欢迎的StepbyStep风格，通过合理的练习引导读者逐步构建在Windows10上运行的应用程序、访问SQLServer数据库以及开发多线程应用等。 全书共27章，结构清晰，叙述清楚。所有练习均在VisualStudio2015简体中文版上进行过全面演练。无论是刚开始接触面向对象编程的新手，还是打算迁移到C#的C、C++或Java程序员，都可以从本书汲取到新的知识。迅速掌握C#编程技术。 目录 第I部分VisualC#和VisualStudio2015概述 第1章欢迎进入C#编程世界3 第2章使用变量、操作符和表达式27 第3章方法和作用域48 第4章使用判断语句72 第5章使用复合赋值和循环语句89 第6章管理错误和异常105 第II部分理解C#对象模型 第7章创建并管理类和对象127 第8章理解值和引用146 第9章使用枚举和结构创建值类型167 第10章使用数组185 第11章理解参数数组204 第12章使用继承215 第13章创建接口和定义抽象类236 第14章使用垃圾回收和资源管理260 第III部分用C#定义可扩展类型 第15章实现属性以访问字段281 第16章使用索引器302 第17章泛型概述317 第18章使用集合344 第19章枚举集合366 第20章分离应用程序逻辑并处理事件379 第21章使用查询表达式来查询内存中的数据406 第22章操作符重载428 第IV部分用C#构建UWP应用 第23章使用任务提高吞吐量451 第24章通过异步操作提高响应速度489 第25章实现UWP应用的用户界面525 第26章在UWP应用中显示和搜索数据567 第27章在UWP应用中访问远程数据库608

Flask是一种具有平缓学习曲线和庞大社区支持的微框架，利用它可以构建大规模的web应用。学习上手Flask非常轻松，但要深入理解却并不容易。 本书从一个简单的Flask应用开始，通过解决若干实战中的问题，对一系列进阶的话题进行了探讨。书中使用MVC（模型-视图-控制器）架构对示例应用进行了转化重构，以演示如何正确地组织应用代码结构。有了可扩展性强的应用结构之后，接下来的章节使用Flask扩展为应用提供了额外的功能，包括用户登录和注册、NoSQL查询、REST API、一套后台管理界面，以及其他特性。然后，你会学到如何使用单元测试，保障代码持续按照正确的方式工作，避免极具风险的猜测式编程。本书最后会讨论可用于部署Flask应用的诸多不同平台，以及你必须考虑的，每个平台的优劣利弊。 目录 第1章 入门 1 第2章 使用SQLAlchemy创建数据模型 11 第3章 通过模板创建视图 29 第4章 使用蓝图创建控制器 52 第5章 进阶的应用结构 58 第6章 保护应用安全 65 第7章 在Flask中使用NoSQL数据库 96 第8章 构建RESTful API 127 第9章 使用Celery编写异步任务 148 第10章 有用的Flask扩展 168 第11章 构建你自己的扩展 192 第12章 测试Flask应用 201 第13章 部署Flask应用 219

Book Description: This book gives you a great selection of recipes to automate your business processes with Python, and provides a platform for you to understand how Python is useful to make time consuming and repetitive business tasks more efficient. Python is a mature high level language, has object-oriented programming features, powers various apps, has a huge set of modules, and great community support. Python is extremely easy to use, can help you get complex tasks done efficiently and is an apt choice for our needs. With a classic problem-solution based approach and real-world examples, you will delve into things that automate your business processes. You will begin by learning about the Python modules to work with Web, Worksheets, Presentations and PDFs. You’ll leverage Python recipes to automate processes in HR, Finance and making them efficient and reliable. For instance, company payroll — an integral process in HR will be automated with Python recipes. A few chapters of this book will also help you gain knowledge on working with bots and computer vision. You will learn how to build bots for automating business use cases by integrating artificial intelligence. You’ll also understand how Python is helpful in face detection and building a scanner of your own. You will see how to effectively and easily use Python code to manage SMS and voice notifications, opening a world of possibilities using cloud telephony to solve your business needs. Moving forward, you will learn to work with APIs, Webhooks and Emails to automate Marketing and Customer Support processes. Finally, using the various Python libraries, this book will arm you with knowledge to customize data solutions and generate reports to meet your business needs. This book will help you up-skill and make your business processes efficient with the various Python recipes covered in this book. What you will learn To automate business processes and make them efficient with Python recipes Explore the power of REST APIs and implement Web hooks. Work with Twitter REST APIs and post automated tweets with Python. Understand the world of Cloud telephony and implement business use cases with SMS and Voice Notification with Python bindings. Manipulate images and learn how to use Python’s Computer Vision for face detection and automate business tasks. Have you thought of making your organisation go paperless? Learn about conversational bots and implement one of your own using Python. You will also learn to integrate AI to your bots. Understand Data analysis and generate interesting insights on your data using Python’s modules for data filtering and visualisation.

书名：Python性能分析与优化 作者：[乌拉圭] Fernando Doglio 译者：陶俊杰　陈小莉 英文版为Mastering Python High Performance

内容简介 　　《利用Python进行数据分析》讲的是利用Python进行数据控制、处理、整理、分析等方面的具体细节和基本要点。同时，它也是利用Python进行科学计算的实用指南（专门针对数据密集型应用）。 　　《利用Python进行数据分析》重点介绍了用于高效解决各种数据分析问题的Python语言和库。《利用Python进行数据分析》没有阐述如何利用Python实现具体的分析方法。 作者简介 　　Wes McKinney，资深数据分析专家，对各种Python库（包括NumPy、pandas、matplotlib以及IPython等）等都有深入研究，并在大量的实践中积累了丰富的经验。撰写了大量与Python数据分析相关的经典文章，被各大技术社区争相转载。开发了用于数据分析的著名开源Python库——pandas，广获用户好评。在创建Lambda Foundry（一家致力于企业数据分析的公司）之前，他曾是AQR Capital Management的定量分析师。 京东购买链接：https://item.jd.com/11352441.html

O'Reilly精品图书系列 利用Python进行数据分析 Python for Data Analysis （美）麦金尼（McKinney,W.）　著 唐学韬　译 完整清晰中文文字版

C#经典实例(第4版)完整版清晰，支持C# 6.0

Programming Python, 4th Edition 中文扫描版 完整版。因文件过大，百度网盘共享，详见附件。

Visual Basic 2005 入门经典（中文版）清晰版（第一部分） 作者:（美）威利斯（Willis，T.），（美）纽萨姆（Newsome，B.）著；李铭译 页数:708 出版社:北京市：清华大学出版社 出版日期:2006 简介:本书讲解VB 2005的基础知识和编程技.

Visual Basic 2005 入门经典（中文版）清晰版（第二部分） 作者:（美）威利斯（Willis，T.），（美）纽萨姆（Newsome，B.）著；李铭译 页数:708 出版社:北京市：清华大学出版社 出版日期:2006 简介:本书讲解VB 2005的基础知识和编程技巧。