Aim : To predict the salary of the job seeking candidate .
Tools used : Python, CSS, HTML, Flask, Sublime text, Jupyter notebook
Techniques used : ML algorithm- Linear regression

This is basically a very simple app that predicts the salary of the candidate by using its Experience(years) , Test score (out of 10) and Interview score(out of 10)

Aim : To Predict Whether the person is suffering from any Heart disease.
Tools used : Python, CSS, HTML, Jupyter notebook, Flask, Sublime text
Techniques used : ML algorithm- Random forest

This is a tools that can analyze whether the person has any cardiac problem or not based on some of the inputs that can be easily calculated by any individual.

Aim : To Predict Whether the person has Diabetes or not .
Tools used : Python, CSS, HTML, Jupyter notebook, Flask, Sublime text
Techniques used : ML algorithm- Random forest

This is a tools that can analyze whether the person has diabetes or not based on the Age, Glucose level and BMI

The model was designed and given to me as a task for the internship to deploy it on AWS . Basic technologies used for deploying are fastapi,(for testing the model), flask and python language.
The final model is deployed on AWS EC2 instance.