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 investigates the impact of wage structure on employee satisfaction, motivation, and retention in Thailand’s textile manufacturing industry. Despite the recognized importance of ...

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 ...

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...

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Abstract: Artificial neural network (ANN) works as a very effective tool in both classification and regression problem. The main advantage lies in the fact that it can draw fine distinctions, patterns ...

Implement Linear Regression in Python from Scratch ! In this video, we will implement linear regression in python from scratch. We will not use any build in models, but we will understand the code ...

Adaptive Lasso is an extension of the standard Lasso method that provides improved feature selection properties through weighted L1 penalties. It assigns different weights to different coefficients in ...