MenuSights

MenuSights is currently two things:

A "real-world" dataset being used to explore and illustrate the utility of deep neural networks and word vector embeddings in extracting cholesterol predictions from the names of food items. This is under development in this Jupyter notebook.
A webtool developed during my time with Insight Health Data Science. It's based on a logistic regression classifier that analyzes names of items on local restaurant menus and provides a prediction as to whether the food is likely to be low, medium, high, or very high in cholesterol. There is a much fuller explanation of how the data were collected and how the model was trained evaluated within the relevant Jupyter notebooks

Name		Name	Last commit message	Last commit date
Latest commit History 18 Commits
Building Menusites webapp		Building Menusites webapp
sklearn_intermediate_models		sklearn_intermediate_models
tf_data		tf_data
.gitignore		.gitignore
MenuSights Logistic Regression Model Building.ipynb		MenuSights Logistic Regression Model Building.ipynb
README.md		README.md
Word2Vec menusights.ipynb		Word2Vec menusights.ipynb
board.png		board.png
checkpoint		checkpoint
paper on rating prediction.pdf		paper on rating prediction.pdf