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A heart disease detection project using machine learning to analyze patient data and predict the likelihood of heart disease. The project aims to aid healthcare professionals in early detection, enabling timely interventions and improving patient outcomes.
This is an End-to-End Data Science project which can predict whether a person has diabetes, or not, based on information about the patient such as blood pressure, body mass index (BMI), age, etc.
This study investigates the quality of exercise using the machine learning algorithms and classifies into varying degrees of effectiveness compared to standard practices. The exercise analyzed is dumbbell pull-ups.
Welcome to InferUSAData, your gateway to insightful data analysis with a focus on the United States. This repository houses a collection of data science projects, each dedicated to uncovering valuable insights from various datasets related to the USA.
Conducted Data Analysis on financial records to gain insight into how to minimize monthly expenditure. Created and trained a linear regression model to forecast expenditure for the following months.