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Python for Biologists: by Dr Martin Jones (Author) a complete programming course for beginners /

By: Contributor(s): Material type: TextTextSeries: Publisher: UK : CreateSpace Independent, 2015Description: 244 pages : illustrations ; 24 cmISBN:
  • 978-1492346135
Other title:
  • Python for data science
Subject(s): DDC classification:
  • 005.133 23 JOP
LOC classification:
  • QA76.73.P98 M376 2015
Contents:
pt. I. Getting started with Python for data science -- Discovering the match between data science and Python -- Introducing Python's capabilities and wonders -- Setting up Python for data science -- Reviewing basic Python -- pt. II. Getting your hands dirty with data -- Working with real data -- Conditioning your data -- Shaping data -- Putting what you know in action -- pt. III. Visualizing the invisible -- Getting a crash course in MatPlotLib -- Visualizing the data -- Understanding the tools -- pt. IV. Wrangling data -- Stretching Python's capabilities -- Exploring data analysis -- Reducing dimensionality -- Clustering -- Detecting outliers in data -- pt. V. Learning from data -- Exploring four simple and effective algorithms -- Performing cross-validation, selection, and optimization -- Increasing complexity with linear and nonlinear tricks -- Understanding the power of the many -- pt. VI. The part of tens -- Ten essential data science resource collections -- Ten data challenges you should take.
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Holdings
Item type Current library Call number Status Date due Barcode
Books Books Central Library, SUST General Stacks 005.133 JOP (Browse shelf(Opens below)) Available 0081845

Includes index.

pt. I. Getting started with Python for data science -- Discovering the match between data science and Python -- Introducing Python's capabilities and wonders -- Setting up Python for data science -- Reviewing basic Python -- pt. II. Getting your hands dirty with data -- Working with real data -- Conditioning your data -- Shaping data -- Putting what you know in action -- pt. III. Visualizing the invisible -- Getting a crash course in MatPlotLib -- Visualizing the data -- Understanding the tools -- pt. IV. Wrangling data -- Stretching Python's capabilities -- Exploring data analysis -- Reducing dimensionality -- Clustering -- Detecting outliers in data -- pt. V. Learning from data -- Exploring four simple and effective algorithms -- Performing cross-validation, selection, and optimization -- Increasing complexity with linear and nonlinear tricks -- Understanding the power of the many -- pt. VI. The part of tens -- Ten essential data science resource collections -- Ten data challenges you should take.

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