Machine Learning Approach

Machine learning (ML) is rapidly transforming diverse scientific fields by enabling efficient data analysis and prediction. Current research focuses on applying ML algorithms, including neural networks (e.g., autoencoders, LSTMs, and gradient boosting trees), to diverse datasets for tasks such as anomaly detection, classification, and regression. These applications range from predicting physical properties and diagnosing diseases to optimizing resource allocation and forecasting events like flight delays or air pollution. The resulting insights and predictive models offer significant advancements in various scientific disciplines and practical applications, improving efficiency, accuracy, and decision-making.