best data science books

:15px "> learning R Blog URL: http://learnr.wordpress.com p26_27 r home page: http://www.r-project.org rstdio home page:/http/ www.rstdio.com/ r Introduction: http://www.cyclismo.org/tutorial/R/ r a relatively complete getting Started Guide: http://www.statmethods.net/about/sitemap.html plyr Reference Document: Http://cran.r-projects.org/web/packages/plyr/plyr.pdf ggplot2 Reference Document: Http://cran.r-project.org/web/packages/ggplot2/gg

#转自wx公众号: Python Developer#问题/answer Source: Quora English: Roman Trusov Bole Online column Author-Xiaoxiaoli Links: http://python.jobbole.com/85704/ "Bole Online Guide": A netizen in Quora asked questions, and added that "I have 10 days of free time, every day want to spend 10 hours to learn the knowledge of data science, should learn something?" Thank you "Bole online excerpts of Rom

you don't like the learning style of interactive coding, you can also learn Google's Python lessons. This 2-day course series contains not only the Python knowledge mentioned earlier, but also some of the things that will be discussed behind it. Step 3: Learn regular expressions in the Python language You will often use regular expressions to clean up data, especially when you are working with text data. T

Data room charging system-the power of Information Science Data room charging system-the power of Information Science The IDC has been dragging on for a long time since the beginning. I feel that I am not doing a lot of work, and I will go back to the third layer to review the design model. Looking at Zhenhua and every

The 1th chapter constructs the experiment environment1-1 guided Video1-2 Anaconda and Jupyter Notebook introduction1-3 Anaconda installation demo on Mac1-4 Anaconda Installing the demo on Windows1-5 Anaconda installation demo on LinuxUse of 1-6 Jupyter-notebook demo2nd Chapter NumPy Introduction2-1 Data Science field 5 common Python libraries2-2 matrix operations for the review of Mathematical fundamentals2

First, IntroductionAs for regular expressions, I have already made a detailed introduction in the previous (Data Science Learning Codex 31), which summarizes the common functions of the self-contained module re in Python.As a module supported by Python for regular expression related functions, re provides a series of methods to complete the processing of almost all types of textual information, as described

Chapter I.1. Anaconda (the most famous Python data science platform)Let's start with the Anaconda.What is Anaconda????Reply:(1), Scientific computing platform(2), there are a lot of convenient bags for us to use(3), cross-platform: Mac \linux\windows(4), most importantly: Open source free of charge and community for small friends to exchange2, Installation Anaconda: https://mirror.tuna.tsinghua.edu.cn/help/

1. Introduction Interactive (interactive) data science and science computing tools, main cell interaction and quick display .It is an Open-source project derived from the IPython.Official Website Address cell interactionAt the command line, interact with the unit of behavior;In the IDE, execute once in the form of a source file.If you want to perform a paragraph

TRUEFALSE TRUEFALSE TRUE> x[good][11245Complete.cases () can also handle matrix data> airquality[1:6,] Ozone SOLAR.R Wind TempMonth Day1 A the 7.4 the 5 12 $ 118 8.0 the 5 23 A 149 12.6 About 5 34 - 313 11.5 + 5 45Na Na14.3 About 5 56 -NA14.9 the 5 6> Airquality[good, [1:6,] Ozone SOLAR.R Wind TempMonth Day1 A the 7.4 the 5 12 $

1. Data Visualization (full color) In the face of complex big data, visualization provides a good interpretation angle and method, and is a powerful tool for big data analysis and application. For the first time, this book comprehensively and meticulously combs the history, theories, tools, and application cases of visualization, as well as illustrations and

The first example we look at in the drafting process, we need a formula: $p ={12\over q}$, then we observe the effect. And then another one that uses \ (to do the inline \ (p={12\over q}\) Latex formula for the delimiterIn the following example, we have a large section of mathematical formulas, and we have another line to show:$$|\vec{a}|=\sqrt{a_x^2 + a_y^2 + a_z^2}.$$These two models are basically enough, and the specific Latex syntax must be self-GoogleUsing Latex to edit paper-level

Python has become increasingly popular among data science enthusiasts, and it is important that it brings a complete system to the universal programming language. With Python you can not only transform operational data, but also create powerful piping commands and machine learning processes in a single system. In Analytics Vidhya, we all like to use Python, and m

Tags: ATI member parent Sea character may GRE manually APIHow does explain machine learning and Data Mining to non computer science people?Pararth Shah, ML enthusiast answered Dec, ShenzhenFeatured on VentureBeat • Upvoted by Melissa Dalis, CS Math Major at Duke and Alberto Bietti, PhD student in Machine learn Ing. Former ML engineer Mango ShoppingSuppose you go shopping for mangoes one day. The ve

the required package again.4, after learning the introductory book, you need to learn how to use Python to do data analysis, recommend a book: using Python for data analysis, this book mainly introduces the data analysis of several commonly used modules: NumPy, pandas, Matplotlib, and data preprocessing required

the Pythonpath:spark installation directory4. Copy the Pyspark packageWrite Spark program, copy pyspark package, add code display functionIn order for us to have code hints and complete functionality when writing Spark programs in pycharm, we need to import the pyspark of spark into Python. In Spark's program, there's a python package called Pyspark.Pyspark BagPython is also easy to import third-party packages, just import the corresponding modules into the specified folder.Windows copies Pyspa

Entry books: In-Depth Data Analysis (Douban)This book is quite simple. The basic content is involved, and it is quite clear. Finally, we talked about R as a plus. Difficulty level: very easy. Beer and diapers (Douban)In this case, things are the most typical examples. Difficulty level: very easy. Data beauty (Douban)Each chapter of an introductory book solve

book operation, the book is already in the box, this command is invalid. Skip this command (it must be DD's mistake ). Input Multiple groups of data, for each group of data: The first line of the input contains an integer N, indicating that there are N operations, no more than 1000 operations The second input line contains an integer m, indicating that DD has m books