#Spam example

This is example program demonstrating how textual information can be used for machine learning using scikit-learn library

Data set is UCI (https://archive.ics.uci.edu/ml/machine-learning-databases/00380/) provided you tube comments which are classified as 1 = spam , 0 = not spam

spam.py is example program from Book "Python Artificial Intelligence Projects for Beginners" by Joshua Eckroth it has been slightly modified to run on python 3.x

How to set up on mac book

1. Install python

brew install python3

This installs python package manager

2. Clone repository

git clone git@github.com:arsalanam/spamexample.git

3. run following commands on terminal to create a virtial environment where pandas , numpy and scikit-learn will get installed

cd spamexample
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

4. run it

python spam.py

5. review code and comments

documentation links

scikit-learn working with textual data : http://scikit-learn.org/stable/tutorial/text_analytics/working_with_text_data.html

scikit-learn Count Vectorizer: http://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html

scikit-learn TDIF Vectorizer :http://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.TfidfVectorizer.html

scikit-learn Ensemble learning and Random forrest:http://scikit-learn.org/stable/modules/ensemble.html#forests-of-randomized-trees