Calories Prediction (ML) Web Application

Introduction

This is a excercise based calories prediction machine learning web application developed using python & deployed in heroku cloud platform using Flask webframework. In this case model developed using RandomForestRegressor, Accuracy : 99.68%.

View Deployed Web Application In Cloud

• Download jupyter notebook & Python files corresponding to model implementation : Click Here

Objectives

• Exploratory data analyse & visualization about the data
• identify the releationship between each attributes
• Implement Regression model
• Evaluate the model
• Deploy model in Heroku cloud platform using Flask webframework

About the Dataset

This Dataset about,

• Burned Calories
• Gender
• Duration
• Heart Rate
• Body Temperature
• Height
• Weight , during a excersise in specific time period.

Tools & Technology

Python

• Flask | Scikit-learn | Pandas | Numpy | Matplotlib | Seaborn | Pickle | Gunicorn

Jupyter Notebook

Google Coloboration

Pycharm IDE

HTML

CSS

Javascipt

Resources

• https://www.python.org/
• https://pypi.org/
• https://id.heroku.com/login
• https://jupyter.org/
• https://www.kaggle.com/
• https://colab.research.google.com/notebooks/intro.ipynb?utm_source=scs-index