Introduction to Machine Learning with Python - A Guide for Data Scientists - Grand Format

Edition en anglais

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Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies... Lire la suite
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Résumé

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.

Caractéristiques

  • Date de parution
    31/07/2016
  • Editeur
  • ISBN
    978-1-4493-6941-5
  • EAN
    9781449369415
  • Format
    Grand Format
  • Présentation
    Broché
  • Nb. de pages
    384 pages
  • Poids
    0.71 Kg
  • Dimensions
    17,7 cm × 23,3 cm × 2,1 cm

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À propos de l'auteur

Biographie de Sarah Guido

Andreas Müller earned a PhD in machine learning from the University of Bonn. After working as a machine learning researcher on computer vision applications at Amazon, he joined the Center for Data Science at New York University. He's also a maintainer and core contributor to scikit-learn. Sarah Guido is a data scientist who has spent a lot of time working with startups, and most recently served as Lead Data Scientist at Bitly.
An accomplished conference speaker, Sarah earned a Master of Science in Information from the University of Michigan.

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