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Python Data Science Handbook
  • Language: en
  • Pages: 548

Python Data Science Handbook

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 m...

Python Data Science Handbook
  • Language: en
  • Pages: 548

Python Data Science Handbook

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 m...

Python Data Science Handbook, Jake VanderPlas, 2017
  • Language: en
  • Pages: 548

Python Data Science Handbook, Jake VanderPlas, 2017

  • Type: Book
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  • Published: 2017-06-07
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  • Publisher: Bukupedia

This is a book about doing data science with Python, which immediately begs the question: what is data science? It’s a surprisingly hard definition to nail down, especially given how ubiquitous the term has become. Vocal critics have variously dismissed the term as a superfluous label (after all, what science doesn’t involve data?) or a simple buzzword that only exists to salt résumés and catch the eye of overzealous tech recruiters. In my mind, these critiques miss something important. Data science, despite its hypeladen veneer, is perhaps the best label we have for the cross-disciplinary set of skills that are becoming increasingly important in many applications across industry and a...

A Whirlwind Tour of Python
  • Language: en

A Whirlwind Tour of Python

  • Type: Book
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  • Published: 2016
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  • Publisher: Unknown

None

Statistics, Data Mining, and Machine Learning in Astronomy
  • Language: en
  • Pages: 552

Statistics, Data Mining, and Machine Learning in Astronomy

As telescopes, detectors, and computers grow ever more powerful, the volume of data at the disposal of astronomers and astrophysicists will enter the petabyte domain, providing accurate measurements for billions of celestial objects. This book provides a comprehensive and accessible introduction to the cutting-edge statistical methods needed to efficiently analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the upcoming Large Synoptic Survey Telescope. It serves as a practical handbook for graduate students and advanced undergraduates in physics and astronomy, and as an indispensable reference for r...

Python for Data Analysis
  • Language: en
  • Pages: 544

Python for Data Analysis

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 IPyt...

Introduction to Machine Learning with Python
  • Language: en
  • Pages: 394

Introduction to Machine Learning with Python

Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with t...

Pythonデータサイエンスハンドブック
  • Language: ja
  • Pages: 560

Pythonデータサイエンスハンドブック

  • Type: Book
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  • Published: 2018-05
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  • Publisher: Unknown

Pythonのデータサイエンス用のツールを使いこなし、効率よく仕事を進めるための、実用的な情報が詰め込まれたリファレンスです。IPythonとJupyter、NumPy、pandas、Matplotlib、scikit‐learnをカバーします。それぞれのトピックについて、押さえておくべき基本、tips、便利なコマンドなどを紹介します。Pythonでデータの操作、変換、可視化、統計的処理、データモデルの構築、科学計算を行う人にとってはいつも手元に置いておきたい「使える」一冊です。

The Data Science Handbook
  • Language: en
  • Pages: 416

The Data Science Handbook

A comprehensive overview of data science covering the analytics, programming, and business skills necessary to master the discipline Finding a good data scientist has been likened to hunting for a unicorn: the required combination of technical skills is simply very hard to find in one person. In addition, good data science is not just rote application of trainable skill sets; it requires the ability to think flexibly about all these areas and understand the connections between them. This book provides a crash course in data science, combining all the necessary skills into a unified discipline. Unlike many analytics books, computer science and software engineering are given extensive coverage...

Data Science from Scratch
  • Language: en
  • Pages: 330

Data Science from Scratch

Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-h...