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Build a Health app to perform health predictions for various scenarios by utilising machine learning algorithms, python libraries and host on a cloud platform with public access.

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RealDreammaker/Machine-Learning-Health-App

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HEALTH APP - MACHINE LEARNING PROJECT

Scope

Build a Health app to perform health predictions for various scenarios by 
utilising machine learning algorithms, python libraries and
host on a cloud platform with public access.

app_intro

Software

Python, Pandas, Seaborn, Matplotlib, Plotly Express, TQDM, Sklearn,  
XGBoost, nltk,  Pickle, Flask API, HTML/CSS/Bootstrap, other.

Datasets

Data Sources

Kaggle
Dataworld

Selected datasets:

Heart Disease
Stress Lysis
Body Performance
Travel Insurance Predictions


Machine Learning Models Overview

Model creation

For exploratory data analysis, train, test, validate and generating models we use Jupiter Notebooks

Stroke Prediction Model
Physical Stress Model
Body Performance Model
Travel Insurance Prediction Model

Heroku Deployment

Heroku_HealthApp
Environment Requirements for app to run on local computer

Presentation slides

Link to Google doc

Visualisations

Stress_Prediction_Stress_Predication_Temperature_vs_Humidity

Stroke_Prediction_Age_Category_Count

Travel_Insurance_Customers_by_Age

Body_Performance_Blood_Presure

About us:

DAJK Team: “Does AI Just Know”? 
Daniela Cornea (DC)
Anh Huong (AH)
Josh Lowe (JL)
Kelvin Nguyen (KN)

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Build a Health app to perform health predictions for various scenarios by utilising machine learning algorithms, python libraries and host on a cloud platform with public access.

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