Objective: Using the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework, this study evaluated the implementation of the virtual COVID-19 HITH service and identified ...
Learn how the Adagrad optimization algorithm works and see how to implement it step by step in pure Python — perfect for beginners in machine learning! #Adagrad #MachineLearning #PythonCoding FBI ...
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 ...
In this tutorial, we will discover how to harness the power of an advanced AI Agent, augmented with both Python execution and result-validation capabilities, to tackle complex computational tasks. By ...
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 ...
In this tutorial, we’ll build a fully functional Retrieval-Augmented Generation (RAG) pipeline using open-source tools that run seamlessly on Google Colab. First, we will look into how to set up ...
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 ...
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: Traditional linear scaling artificial neural network (ANN)-based compact models face significant challenges in achieving high accuracy for device modeling. To overcome this limitation, a ...
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