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This repository contains the Supplementary Material for the book "Applied Machine Learning with Python", written by Andrea Giussani. You can find details about the book on the BUP website.
The books was written with the following specific versions of some popular libraries:

• scikit-learn version 0.21.3
• pandas version 0.23.1
• numpy version 1.16.4
• xgboost version 0.82
• nltk version 3.3
• gensim version 3.1.8
• matplotlib version 3.1.0
• seaborn version 0.9.0

The book provides a book-specific module, called egeaML. To install it into your local environment, use the command

pip install git+https://github.com/andreagiussani/Applied_Machine_Learning_with_Python.git

or using Anaconda:

conda install git+https://github.com/andreagiussani/Applied_Machine_Learning_with_Python.git

To install the necessary requirements, run this command from your favourite terminal emulator:

pip install -r requirements.txt

If you have Python3 already installed in your local environment:

python3 -m pip install --upgrade pip
python3 -m pip install git+https://github.com/andreagiussani/Applied_Machine_Learning_with_Python.git

To use it inside your Python3 environment, you should initialise the class as follows:

import egeaML as eml

or alternatively

from egeaML import *
from egeaML import DataIngestion

If you have errata for the book, please submit them via the BUP website. In case of possible mistakes within the book-specific module, you can submit a fixed-version as a pull-request in this repository.

@book{giussani2019,
	TITLE="Applied Machine Learning with Python",
	AUTHOR="Andrea Giussani",
	YEAR="2019",
	PUBLISHER="Bocconi University Press"
}