Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
Abstract: Detecting anomalies in general ledger data is of utmost importance to ensure the trustworthiness of financial records. Financial audits increasingly rely on machine learning (ML) algorithms ...
Abstract: The recent AI development has provided effective solutions to address current problems and improve decision making process. The article takes a case study in Data and Information Centre ...
Background: Stroke is one of the leading causes of death and disability worldwide, making early screening and risk prediction crucial. Traditional methods have limitations in handling nonlinear ...
For each league, the application computes several statistics (features) about the teams, including their form, the performance of the last N matches, etc. The stats are computed for both the home team ...
Objective: This study aims to identify the key risk factors for occupational exposure among oral healthcare workers and develop a predictive model using machine learning algorithms to lay the ...
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