omarsar/data_mining_2017_fall_nthu.md

## data_mining_2017_fall_nthu.md

      
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    Computing Resources


Operating system: Preferably Linux or MacOS. If you have Windows, things may crash unexpectedly (try installing a virtual machine if you need to)
RAM: Minimum 8GB
Disk space: Mininium 8GB


Software Requirements

Here is a list of the required programs and libraries necessary for this lab session. (Please install them before coming to our lab session on Tuesday; this will save us a lot of time, plus these are the same libraries you may need for your first assignment).

Python 3+ (Note: lab and assignment will be done strictly using Python 3)

Install latest version of Python 3


Anaconda environemnt or any other environment (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


Test script

Open a jupyter notebook and run the following commands. If you have properly installed all the necessary libraries, you shouldn't have any problems running the code below.
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

Preview of Complete Jupyter Notebook (Coming Soon)

Please note that we will upload the jupyter notebook that will be used as guide on both this page Githug page and our lab's organization page. (We will provide the link on the day of the lab session). Additional instructions for assignments will be posted there, and submissions will more than likely be required to be posted through Github. In other words, if you don't have an account yet, please create a Github account in advance. We will try to give a short session on how to use git to upload your individual assignments, but we cannot guarantee this because of the limited time we have for the lab session.
Don't worry! You will have plenty of time to learn Git before the assignment's due date. Another option would be to have a short mini lab after this one or we can provide an online session; we will talk about this during the lab session. For the meanwhile, this tutorial will help you get started. Learning how to do version control and upload code using git will be useful for other courses in the future so if you want to take your skills to the next level, you can try this online course offered by Codecademy.
One more thing: I have setup a Slack page where we can engage (chat) or just in case anyone has any questions or concerns throughout the course. In Slack you can also setup groups amongst your classmates and get to know each other better. From my experience, these tools are very helpful to get help from TAs and other classmates. This chat room will definitely be super helpful for when the project and exam time comes around. Come say 👋 if you are interested in joining the conversation. I will send an invite to your emails (provided by the iLMS). If you don't receive an invite by Friday (22/09/2017) night, check your spam or comment your email below.
Good luck!