This repository contains all the instructions and necessary code for Data Mining 2017 (Fall) lab session.
- Operating system: Preferably Linux or MacOS
- RAM: 8GB
- Disk space: Minimum 8GB
Here is a list of the required programs and libraries necessary for this lab session:
- Python 3+ (Note: coding will be done strictly on Python 3)
- Install latest version of Python 3
- Anaconda environemnt or any other environement (recommended but not required)
- Install anaconda environment
- Jupyter (Strongly recommended but not required)
- Install jupyter
- Scikit Learn
- Install
sklearn
latest python library
- Install
- Pandas
- Install
pandas
python library
- Install
- Numpy
- Install
numpy
python library
- Install
- Matplotlib
- Install
maplotlib
for python
- Install
- Plotly
- Install and signup for
plotly
- Install and signup for
- NLTK
- Install
nltk
library
- Install
- WordCloud
- Install library for generating word clouds
Open a Jupyter notebook and run the following commands. If you have properly installed all the necessary libraries you should see no error.
import pandas as pd
import numpy as np
import nltk
from sklearn.datasets import fetch_20newsgroups
from sklearn.feature_extraction.text import CountVectorizer
import plotly.plotly as py
import plotly.graph_objs as go
import math
%matplotlib inline
from wordcloud import WordCloud
# my functions
import helpers.data_mining_helpers as dmh
import helpers.text_analysis as ta
https://github.com/omarsar/data_mining_2017_fall_lab/blob/master/news_data_mining.ipynb