Developed an end-to-end customer churn prediction ML pipeline using Python, pandas, and scikit-learn. Implemented and trained a logistic regression model, then deployed it as a REST API service using ...

A burst of experimentation followed ChatGPT's release to the public in late 2022. Now many people are integrating the newest models and custom systems into what they do all day: their work. Chefs are ...

🫀 A machine learning project using logistic regression to predict heart disease risk from clinical data. Built with Python, scikit-learn, and Jupyter notebooks. Achieves 85%+ accuracy on 303-patient ...

Abstract: Optimization algorithms are essential for machine learning models to enhance prediction accuracy. There is a surge in the number of people suffering from diabetes in this present day, it is ...

Learn how to implement Logistic Regression from scratch in Python with this simple, easy-to-follow guide! Perfect for beginners, this tutorial covers every step of the process and helps you understand ...

ABSTRACT: Road traffic accidents are one of the global safety and socioeconomic challenges. According to WHO (2024), it has caused over 1.19 million annual fatalities. It is also projected to cause ...

Background: Sepsis is a life-threatening disease associated with a high mortality rate, emphasizing the need for the exploration of novel models to predict the prognosis of this patient population.

1 Department of Mobility and Infrastructure Planning and Management, College of Urban Development and Engineering, Ethiopian Civil Service University, Addis Ababa, Ethiopia 2 Faculty of Civil ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of k-nearest neighbors regression to predict a single numeric value. Compared to other machine learning ...