The purpose of this project is to use machine learning to power an application that recommends new menu items based on foods you already love as well as similair items.
| Name | Github Page | Personal Website |
|---|---|---|
| Misha Berrien | mishaberrien | www.mishaberrien.com |
- Machine Learning
- Predictive Modeling
- Natural language processing
- item-item based collaborative filtering
- Python
- NumPy
- Pandas
- NLTK
- Selenium
- Scrapy
- Google Colab
- Jupyter notebook
(Provide more detailed overview of the project. Talk a bit about your data sources and what questions and hypothesis you are exploring. What specific data analysis/visualization and modelling work are you using to solve the problem? What blockers and challenges are you facing? Feel free to number or bullet point things here)
- Clone this repo (for help see this tutorial).
- Raw Data is being kept here within this repo.
- Data processing/transformation scripts are being kept here
- In order to run the scripts you'll need to change the data location name to the
data-samplefolder.
This file structure is based on the DSSG machine learning pipeline.