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Machine Learning for Healthcare Analytics Projects

You're reading from   Machine Learning for Healthcare Analytics Projects Build smart AI applications using neural network methodologies across the healthcare vertical market

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781789536591
Length 134 pages
Edition 1st Edition
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Author (1):
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Eduonix Learning Solutions Eduonix Learning Solutions
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Toc

Introduction to the dataset

Our next step is to import the Pima Indians diabetes dataset, which contains the details of about 750 patients:

  1. The dataset that we need can be found at https://raw.githubusercontent.com/jbrownlee/Datasets/master/pima-indians-diabetes.data.csv. We can import it by using the following line:
url = "https://raw.githubusercontent.com/jbrownlee/Datasets/master/pima-indians-diabetes.data.csv"
  1. If we navigate to the preceding URL, we can see a lot of raw information. Once we have imported the dataset, we have to define column names. We will do this using the following lines of code:
names = ['n_pregnant', 'glucose_concentration', 'blood_pressure (mm Hg)', 'skin_thickness (mm)', 'serum_insulin (mu U/ml)', 'BMI', 'pedigree_function', 'age', 'class']

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You have been reading a chapter from
Machine Learning for Healthcare Analytics Projects
Published in: Oct 2018
Publisher: Packt
ISBN-13: 9781789536591
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