Lab 01: Conda Environment and Python Refresher¶
Welcome to CITS4012 Natural Language Processing. NLP is a very practical discipline that requires familiarity with Python, Numpy, Pandas and many similar yet distinctive text processing packages. So let’s started by getting used to handle multiple environments as often different NLP toolkits have conflict requirement on package or Python versions. Then we will move on with some refresher of Python and Numpy.
Google Colab¶
For quick code testing without worrying too much about installing packages, one can use Google Colaboratory, “Colab” for short. If you are not familar with Colab, please follow the intructions to either create a Jupyter Notebook or look through the sample ones.
Bring you own device¶
The following two pages contain instructions on how to set up multiple “isolated” Python environments on your own computer. This is the recommended mode of study because as system adminstrator you have a lot more control on what you can install and when, and the kernerls will not disconnect with a time limit like Google Colab. Fluency in managing multiple environments is also a desired learning outcome of this unit. So despite it can be frustrating and tedious at times, it is rewarding to manage your own coding environment. Please do remember to make use of repositories such as Github for regular backups.