Lab For Data Mining 2017 Fall @ NTHU

This repository contains all the instructions and necessary code for Data Mining 2017 (Fall) lab session.

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Computing Resources

• Operating system: Preferably Linux or MacOS
• RAM: 8GB
• Disk space: Minimum 8GB

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Software Requirements

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
• Pandas
  • Install pandas python library
• Numpy
  • Install numpy python library
• Matplotlib
  • Install maplotlib for python
• Plotly
  • Install and signup for plotly
• NLTK
  • Install nltk library

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Test script

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

# my functions
import helpers.data_mining_helpers as dmh
import helpers.text_analysis as ta

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Preview of Complete Jupyter Notebook

https://github.com/omarsar/data_mining_2017_fall_lab/blob/master/news_data_mining.ipynb