Just saw this announcement from Jason Brownlee. Have read some of his previous works, nicely done. This intro starts where it should, at data preparation and understanding. Much more, including examples at the link.
Data Preparation for Machine Learning
Data Cleaning, Feature Selection, and Data Transforms in Python
Data Preparation for Machine Learning
By Jason Brownlee
$37 USD
Data preparation involves transforming raw data in to a form that can be modeled using machine learning algorithms.
Cut through the equations, Greek letters, and confusion, and discover the specialized data preparation techniques that you need to know to get the most out of your data on your next project.
Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover how to confidently and effectively prepare your data for predictive modeling with machine learning.
About this Ebook:
Read on all devices: English PDF format EBook, no DRM.
Tons of tutorials: 30 step-by-step lessons, 398 pages.
Foundations: intuitions feature selection, scaling, more.
Working code: 168 Python (.py) code files included.
Clear, Complete End-to-End Examples.
Convinced?
Click to jump straight to the packages. ... "
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