These Python notebooks serve as a ground-up educational resource to work through NLP with minimal prior experience/setup. Also included are sets of python and NLP templates to be used piecemeal in my other projects. This repo is a hybridization of Stanford course learnings, personal research, and my condensed notes from the "NLP-Natural Language Processing with Python" course by Jose Portilla with Pierian Data.
*Setup instructions are for MacOS, but can be easily extrapolated to a linux shell on any OS.
1. Use Linux/Terminal to clone the repository into a local directory and cd there.
2. Install Anaconda and initialize as desired.
-I used conda init bash . This adds code to your .bash_profile which activates the base environment by default. This post describes how to suppress this automatic env activation.
-Ensure the (base) environment tag appears before your next command prompt line, or activate the env manually (conda activate base).
3. Create(conda env create -f nlp_ipynb_env.yml) and activate(conda activate nlp_ipynb) the (nlp_ipynb) Python environment. The (nlp_ipynb) tag should appear before your next command prompt line.
4. From the nlp_ipynb directory & environment, type jupyter notebook to open the notebooks in a browser.
##Usage
-Folders are numbered in order of increasing difficulty/complexity.
-Those new to Python should be able to start here from scratch.
-In each notebook, hit shift + enter or command/control + enter to see function output. \
##Extra Links
-Remove DS_Store files and stop automatic .DS_Store creation
-Converting jupyter notebooks between formats and an Intro to jupytext, the tool I used. \
###Environments
-Update existing Conda environment
-CRUD guide for Python Environments