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 3.8.1
- matplotlib version 3.1.0
- seaborn version 0.9.0
The book provides a book-specific module, called egeaML.
Please, clone on your local machine this repo, as follows:
git clone https://github.com/andreagiussani/Applied_Machine_Learning_with_Python.gitTo install it into your local env, I recommend to create a virtualenv where you add the necessary requirements, running this command from your favourite terminal emulator:
pip install -r requirements.txt
pip install git+https://github.com/andreagiussani/Applied_Machine_Learning_with_Python.gitIf, instead, you use the Anaconda system:
conda install --file requirements.txt
conda install git+https://github.com/andreagiussani/Applied_Machine_Learning_with_Python.git
If you have Python3 already installed in your local environment, you can run:
python3 -m pip install --upgrade pip
python3 -m pip install git+https://github.com/andreagiussani/Applied_Machine_Learning_with_Python.gitTo use it inside your Python3 environment, you should initialise the class as follows:
import egeaML.egeaML as emlor alternatively
from egeaML.egeaML import *
from egeaML.egeaML import DataIngestionIf you wish to use the egeaML library on a Jupyter notebook, you firstly need to install the jupyter using
pip install jupyter
python3 -m ipykernel install --user --name=<YOUR_ENV>and then you are ready to use all the feature of this helper.
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{giussani2020,
TITLE="Applied Machine Learning with Python",
AUTHOR="Andrea Giussani",
YEAR="2020",
PUBLISHER="Bocconi University Press"
}