Calories Burnt Prediction using Machine Learning Algorithm

Machine learning algorithm used Random Forest Regressor

Takes 7 input values i.e. Gender,Age,Height,Weight,Duration,Heart Rate,Body Temprature.
Machine Learning algorithm used for regression task.
A random forest is a meta estimator that fits a number of classifying decision trees on various sub-samples of the dataset and uses averaging to improve the predictive accuracy and control over-fitting.
n_estimators = 10 used.
used pickle to dump the model for creating a .pkl file to be read by flask web application.
used flask web framework for deploying the model locally.
created a Landing page using frontend technologies HTML forms and for designing CSS.
used HTML forms to take user input.
after entering details in forms submit button routes the predict METHOD in the app.py i.e. flask web application

One-hot Encoding is a type of vector representation in which all of the elements in a vector are 0, except for one, which has 1 as its value, where 1 represents a boolean specifying a category of the element.

Before	After
Female	1
Male	0

Name		Name	Last commit message	Last commit date
Latest commit History 11 Commits
images		images
static		static
templates		templates
.gitignore		.gitignore
Calories Burnt Prediction.ipynb		Calories Burnt Prediction.ipynb
README.md		README.md
app.py		app.py
calories.csv		calories.csv
exercise.csv		exercise.csv