Shaina Bagri
Helene Willits
Rachel Castellino
This repository is designed to provide an introduction to Natural Language Processing. The introductory notebook (titled NLPConceptual) is meant to provide an overview of Natural Language Processing that can be understood by anyone, regardless of their technical understanding of computer science or mathematics. This notebook covers topics such as the history of NLP, Natural Language Understanding, Natural Language Generation the ethics of NLP, the limitations of NLP, and further reading for curious users. The implementation notebook is a deep dive into Natural Language Processing that gives users the opportunity to build their own Natural Language Processing model and perform word prediction, similar to the word prediction algorithms that are used in modern day texting applications. The second notebook also includes additional NLP project ideas that the user can explore if they want to continue learning more about NLP.
- Fork the notebook using the "fork" button in the upper right-hand side of this page. This will create a copy in your GitHub that you can modify.
GitHub will store a remote version of your code for you, but you will need an application that will allow you to modify and run the code. Now we will connect our GitHub repository to an application that can do this.
- Once you are in your personal copy of the repository, click the "clone" button and copy the link that is provided (you can do this by clicking the copy button right next to the URL address listed).
There are various applications that will run your code, but we recomend using JupyterHub, since it is made by the company who designed these types of notebooks.
- Make a Jupyter Notebook account and log in. They will provide you with a server that you will need to start each time you access your JupyterHub files. Start the server when prompted.
- Once you have access to your empty JupyterHub folder, click on the "new" button in the upper right hand corner and select "terminal." This will open a new page for you where you can code directly in your JupyterHub directory.
- type "git clone " followed by the link that you copied in step 2. You can use command-v or control-v to paste from your clipboard. It should look something like this:
git clone https://github.com/your-github-username/Natural-Language-Processing-Research
- Now, you have created a local copy of your remote GitHub repository. Go back to the tab that shows your JupyterHub. It should now have a folder called Natural-Language-Processing-Research that contains all of the files in your GitHub. You can click to view any of these files. See the demo linked above for a tutorial on how to run code in the second notebook.
- If you have made any changes to the files, you can update those changes in your GitHub repository using the following commands in the terminal that we accessed earler:
git add .
git commit -m "some message here
git push
That's it! Enjoy working with Natural Language Processing!