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Hands-On Predictive Analytics with Python
book

Hands-On Predictive Analytics with Python

by Alvaro Fuentes
December 2018
Beginner to intermediate content levelBeginner to intermediate
330 pages
8h 32m
English
Packt Publishing
Content preview from Hands-On Predictive Analytics with Python

Creating your first ML model

In this section, we will build and implement the code in our first ML model. We will use the diamond prices dataset. Before moving on, let's load the libraries we will use in this notebook:

import numpy as npimport pandas as pdimport matplotlib.pyplot as pltimport seaborn as snsimport os%matplotlib inline

Now, load the diamonds dataset and apply the transformations we have done before:

DATA_DIR = '../data'FILE_NAME = 'diamonds.csv'data_path = os.path.join(DATA_DIR, FILE_NAME)diamonds = pd.read_csv(data_path)## Preparation done from Chapter 2diamonds = diamonds.loc[(diamonds['x']>0) | (diamonds['y']>0)]diamonds.loc[11182, 'x'] = diamonds['x'].median()diamonds = diamonds.loc[~((diamonds['y'] > 30) | (diamonds['z'] ...
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Publisher Resources

ISBN: 9781789138719Supplemental Content