We aim to predict the amount of food and predict their qualities in domains like community kitchen, restaurant, school/collage mess and all of the food industry by utilizing supervised machine learning.If we could accurately predict the amount of raw materials and thereby the amount of food through everyday analysis we can minimise the quantity of food waste drastically and thereby provide for the needy. Supervised Machine Learning has lately proved to be one of the most prominent and efficiently improving methods comprising of several solid techniques and algorithms for the classification, manipulation, and reorganization of databases using the concepts recursive learning.
1.C B Dev Narayan
2.Abhishek P
3.Noble Austine
4.Abhin P T
Empty Bin-Food Quantity Prediction
Quantity of food produced:
we intent to build a supervised machine learning model, trained using a general
Dataset regarding the demand for food and can predict the quantity of food
required for a given set of variables
The trained model can later be fine tuned using the data of a specific location so
that the produce more locally accurate results
The algorithm used for learning is based on naive bayes and logistic regression
classifiers
Neural network:
PyTorch
PyTorch Lightning
Tech Stacks:
tkinter
pandas
Instructions for setting up project
- clone the repository using :
- Make sure that python version 3.6 is installed ''' git clone https://github.com/abhin2002/magnathon-Hello-World'''
- install the dependecies: '''
- pip3 install torch torchvision torchaudio
- pip install pytorch_lightning
- pip install pandas '''
- Go the directory where the project has been cloned
- run on command line : **python .\app.py **
Provide any other links ( for eg. Wireframe , UI )