1. Load the dataset into a DataFrame and explore its contents to understand the data structure. 2.Separate the dataset into independent (X) and dependent (Y) variables, and split them into training ...

1 Manchester Regional High School Science Department, Haledon, USA.

Running Python scripts is one of the most common tasks in automation. However, managing dependencies across different systems can be challenging. That’s where Docker comes in. Docker lets you package ...

Abstract: Using copulas in statistics evaluates the dependence between random variables. Copula modeling has significantly been used in many areas, especially in the search for multivariate ...

Spam Email Detection using Logistic Regression Project Overview This project implements a logistic regression-based classifier to detect spam emails. The dataset is preprocessed, standardized, and ...

1 Institute of Geology and Geophysics, Ministry of Science and Education, Baku, Azerbaijan 2 School of Mining and Geosciences, Nazarbayev University, Astana, Kazakhstan In recent years, seismological ...

Abstract: This paper presents a pulse-arrival-time (PAT) estimation scheme using Extreme Gradient Boosting (XGBoost) regression and its implementation with hardware description language (HDL). PAT is ...

In this tutorial, we demonstrate how to efficiently fine-tune the Llama-2 7B Chat model for Python code generation using advanced techniques such as QLoRA, gradient checkpointing, and supervised ...

In the age of data-driven decision-making, access to high-quality and diverse datasets is crucial for training reliable machine learning models. However, acquiring such data often comes with numerous ...