反馈文件质量
nexusstc/Introduction to Machine Learning with Python: A Guide for Data Scientists/76907dd28aac646353c5b57dd3867c72.mobi
Introduction to Machine Learning with Python : A Guide for Data Scientists 🔍
Andreas C. Müller, Sarah Guido O'Reilly Media; O'Reilly Media, Inc., 1, FR, 2016
英语 [en] · MOBI · 81.5MB · 2016 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/zlib · Save
描述
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 the NumPy and matplotlib libraries will help you get even more from this book.
With this book, you’ll learn:
* Fundamental concepts and applications of machine learning
* Advantages and shortcomings of widely used machine learning algorithms
* How to represent data processed by machine learning, including which data aspects to focus on
* Advanced methods for model evaluation and parameter tuning
* The concept of pipelines for chaining models and encapsulating your workflow
* Methods for working with text data, including text-specific processing techniques
* Suggestions for improving your machine learning and data science skills
备用文件名
lgli/A Guide for Data Scientists 1st _2016 - 1449369413.mobi
备用文件名
lgrsnf/A Guide for Data Scientists 1st _2016 - 1449369413.mobi
备用文件名
zlib/Computers/Artificial Intelligence (AI)/Andreas C. Müller, Sarah Guido/Introduction to Machine Learning with Python: A Guide for Data Scientists_2773766.mobi
备选标题
Введение в машинное обучение с помощью Python: руководство для специалистов по работе с данными: [полноцветное издание]
备选作者
Андреас Мюллер, Сара Гвидо; [перевод с английского и редакция А. В. Груздева]
备选作者
Andreas C. Mueller, Sarah Guido
备选作者
Müller, Andreas, Guido, Sarah
备选作者
Мюллер, Андреас
备用出版商
O'Reilly Media, Incorporated
备用出版商
Диалектика
备用版本
First edition, third release, Sebastopol, CA, 2017
备用版本
United States, United States of America
备用版本
O'Reilly Media, Sebastopol, CA, 2017
备用版本
First edition, Sebastopol, CA, 2016
备用版本
First edition, Beijing, 2016
备用版本
Москва [и др.], Russia, 2017
备用版本
September 25, 2016
元数据中的注释
0
元数据中的注释
lg1565355
元数据中的注释
{"edition":"1","isbns":["1449369413","9781449369415"],"last_page":400,"publisher":"O'Reilly Media"}
元数据中的注释
Предм. указ.: с. 465-472
Пер.: Müller, Andreas C. Introduction to machine leaning with Python Beijing [etc.] : O'Reilly, cop. 2017 978-1-449-36941-5
元数据中的注释
РГБ
元数据中的注释
Russian State Library [rgb] MARC:
=001 008925002
=005 20180420133212.0
=008 170623s2017\\\\ru\||||\\\\\\\0||\|\rus|d
=017 \\ $a КН-П-18-028128 $b RuMoRKP
=017 \\ $a 17-47693 $b RuMoRKP
=020 \\ $a 978-5-9908910-8-1 $c 1000 экз.
=040 \\ $a RuMoRGB $b rus $e rcr $d RuMoRGB
=041 1\ $a rus $h eng
=044 \\ $a ru
=084 \\ $a З973.2-018.19Python,0 $2 rubbk
=100 1\ $a Мюллер, Андреас
=245 00 $a Введение в машинное обучение с помощью Python $h [Текст] : $b руководство для специалистов по работе с данными : [полноцветное издание] $c Андреас Мюллер, Сара Гвидо ; [перевод с английского и редакция А. В. Груздева]
=260 \\ $a Москва [и др.] $b Диалектика $c 2017
=300 \\ $a 472, [1] с. $b ил., табл., цв. ил. $c 24 см
=336 \\ $a текст (text) $b txt $2 rdacontent
=337 \\ $a неопосредованный (unmediated) $b n $2 rdamedia
=338 \\ $a том (volume) $b nc $2 rdacarrier
=500 \\ $a Предм. указ.: с. 465-472
=534 \\ $p Пер.: $a Müller, Andreas C. $t Introduction to machine leaning with Python $c Beijing [etc.] : O'Reilly, cop. 2017 $z 978-1-449-36941-5
=650 \7 $a Вычислительная техника -- Вычислительные машины электронные цифровые -- Программирование -- Языки программирования -- Python -- Пособие для специалистов $2 rubbk
=650 \7 $a PYTHON, язык программирования $0 RU\NLR\AUTH\661326547 $2 nlr_sh
=700 1\ $a Гвидо, Сара
=852 \\ $a РГБ $b FB $j 2 17-43/104 $x 90
=852 7\ $a РГБ $b CZ2 $h З973.2-018/М98 $x 83
=852 \\ $a РГБ $b FB $j 2 18-18/413 $x 90
备用描述
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 Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.
With this book, you'll learn:
Fundamental concepts and applications of machine learning
Advantages and shortcomings of widely used machine learning algorithms
How to represent data processed by machine learning, including which data aspects to focus on
Advanced methods for model evaluation and parameter tuning
The concept of pipelines for chaining models and encapsulating your workflow
Methods for working with text data, including text-specific processing techniques
Suggestions for improving your machine learning and data science skills
备用描述
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 the NumPy and matplotlib libraries will help you get even more from this book. -- Provided by publisher
开源日期
2016-10-08
更多信息……

🚀 快速下载

成为会员以支持书籍、论文等的长期保存。为了感谢您对我们的支持，您将获得高速下载权益。❤️

🐢 低速下载

由可信的合作方提供。 更多信息请参见常见问题解答。 （可能需要验证浏览器——无限次下载！）

所有选项下载的文件都相同，应该可以安全使用。即使这样，从互联网下载文件时始终要小心。例如，确保您的设备更新及时。
显示外部下载
  • 对于大文件，我们建议使用下载管理器以防止中断。
    推荐的下载管理器：JDownloader
  • 您将需要一个电子书或 PDF 阅读器来打开文件，具体取决于文件格式。
    推荐的电子书阅读器：Anna的档案在线查看器、ReadEra和Calibre
  • 使用在线工具进行格式转换。
    推荐的转换工具：CloudConvert和PrintFriendly
  • 您可以将 PDF 和 EPUB 文件发送到您的 Kindle 或 Kobo 电子阅读器。
    推荐的工具：亚马逊的“发送到 Kindle”和djazz 的“发送到 Kobo/Kindle”
  • 支持作者和图书馆
    ✍️ 如果您喜欢这个并且能够负担得起，请考虑购买原版，或直接支持作者。
    📚 如果您当地的图书馆有这本书，请考虑在那里免费借阅。