Abstract: The high performance of conventional model predictive control (CMPC) for electric drives depends on the fidelity of the machine’s parametric model. However, the parameters of the interior ...
A comprehensive Artificial Neural Network project for predicting customer churn using deep learning.
This project implements an Artificial Neural Network (ANN) to predict whether a customer will leave a bank. It includes model training, evaluation, and deployment with an interactive Streamlit web ...
In this tutorial, we show how we treat prompts as first-class, versioned artifacts and apply rigorous regression testing to large language model behavior using MLflow. We design an evaluation pipeline ...
Abstract: This study employs artificial neural networks (ANNs) to predict the dielectric properties of nanofluids (NFs) formulated with mineral oils, synthetic esters, and natural esters. Individual ...
ABSTRACT: Heart disease remains one of the leading causes of mortality worldwide, accounting for millions of deaths annually. Early detection of individuals at risk is essential for reducing ...
This project implements full-batch gradient descent (FBGD) for linear regression, comparing CPU serial and GPU implementations. The assignment demonstrates: assignment-5-linear-regression/ ├── ...
Learn how to build a simple linear regression model in C++ using the least squares method. This step-by-step tutorial walks you through calculating the slope and intercept, predicting new values, and ...
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