Beginning Data Science with Python and Jupyter (Packt)
Thursday, 18 October 2018

This step-by-step guide is aimed at beginners who know a little Python and are looking for a quick, fast-paced introduction. Author Alex Galea explores machine learning models with real datasets. The book ends by showing how easy it can be to scrape and gather data from the open web.

<ASIN:1789532027>

Author: Alex Galea
Publisher: Packt Publishing
Date: June 2018
Pages: 194
ISBN: 978-1789532029
Print: 1789532027
Kindle: B07DNJ9KKL
Audience: Python developers
Level: Introductory
Category: Data Science 

 

  • Identify potential areas of investigation and perform exploratory data analysis
  • Plan a machine learning classification strategy and train classification models
  • Use validation curves and dimensionality reduction to tune and enhance your models
  • Scrape tabular data from web pages and transform it into Pandas DataFrames
  • Create interactive, web-friendly visualizations to clearly communicate your findings

For recommendations of books on big data, see Reading Your Way Into Big Data. For recommendations of Python books see Books for Pythonistas and Python Books For Beginners in our Programmer's Bookshelf section.

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