Building machine learning systems with Python

Building machine learning systems with Python: get more from your data through creating practical machine learning systems with Python

by Coelho, Luis Pedro

Type Book
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This book primarily targets Python developers who want to learn and use Python's machine learning capabilities and gain valuable insights from data to develop effective solutions for business problems.

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Title Statements

  • Full title :Building machine learning systems with Python : get more from your data through creating practical machine learning systems with Python / Luis Pedro Coelho, Willi Richert.

Summary

This book primarily targets Python developers who want to learn and use Python's machine learning capabilities and gain valuable insights from data to develop effective solutions for business problems.

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Edition Statements

  • Publication Date:2015.
  • Edition:Second edition

Publication Statements

  • Publisher(s):Packt Publishing
  • Place of Publication:Birmingham, UK
  • Language:eng
  • Publication Date:2015.

Notes

Includes index.

The Physical Object

  • Description:1 online resource (1 volume) : : illustrations

Edition Identifiers

  • ISBN:9781784392888, 178439288X, 1784392774, 9781784392772
  • oclc:ocn908029893
  • LC Classification:QA76.73.P98
  • Dewey Decimal:006.76

Table of Contents

Machine generated contents note: ch. 1 Getting Started with Python Machine Learning -- Machine learning and Python -- a dream team -- What the book will teach you (and what it will not) -- What to do when you are stuck -- Getting started -- Introduction to NumPy, SciPy, and matplotlib -- Installing Python -- Chewing data efficiently with NumPy and intelligently with SciPy -- Learning NumPy -- Indexing -- Handling nonexisting values -- Comparing the runtime -- Learning SciPy -- Our first (tiny) application of machine learning -- Reading in the data -- Preprocessing and cleaning the data -- Choosing the right model and learning algorithm -- Before building our first model ... -- Starting with a simple straight line -- Towards some advanced stuff -- Stepping back to go forward -- another look at our data -- Training and testing -- Answering our initial question -- Summary -- ch. 2 Classifying with Real-world Examples -- The Iris dataset -- Visualization is a good first step

Note continued: Building our first classification model -- Evaluation -- holding out data and cross-validation -- Building more complex classifiers -- A more complex dataset and a more complex classifier -- Learn…

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Subjects

Apprentissage automatique -- Développem… Machine learning -- Development Python (Computer program language) Python (Langage de programmation)

Writers

Coelho, Luis Pedro Richert, Willi

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