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The Supervised Learning Workshop

You're reading from   The Supervised Learning Workshop Predict outcomes from data by building your own powerful predictive models with machine learning in Python

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Product type Paperback
Published in Feb 2020
Publisher Packt
ISBN-13 9781800209046
Length 532 pages
Edition 2nd Edition
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Authors (4):
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Blaine Bateman Blaine Bateman
Author Profile Icon Blaine Bateman
Blaine Bateman
Ashish Ranjan Jha Ashish Ranjan Jha
Author Profile Icon Ashish Ranjan Jha
Ashish Ranjan Jha
Ishita Mathur Ishita Mathur
Author Profile Icon Ishita Mathur
Ishita Mathur
Benjamin Johnston Benjamin Johnston
Author Profile Icon Benjamin Johnston
Benjamin Johnston
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Toc

1. Fundamentals

Overview

This chapter introduces you to supervised learning, using Anaconda to manage coding environments, and using Jupyter notebooks to create, manage, and run code. It also covers some of the most common Python packages used in supervised learning: pandas, NumPy, Matplotlib, and seaborn. By the end of this chapter, you will be able to install and load Python libraries into your development environment for use in analysis and machine learning problems. You will also be able to load an external data source using pandas, and use a variety of methods to search, filter, and compute descriptive statistics of the data. This chapter will enable you to gauge the potential impact of various issues such as missing data, class imbalance, and low sample size within the data source.

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