Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Felimban, R. (2025) Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms.

Understanding how ozone behaves indoors is vital for assessing human health risks, as people spend most of their time inside.

The AI’s learned behavior shows a clear preference for high-density, mixed-use development, increasing the spatial clustering ...

Here are 11 free NPTEL data science and analytics courses from leading IITs cover graph theory, Bayesian modelling, Python, R ...

Traditional financial distress prediction relies heavily on backward-looking financial indicators such as leverage, liquidity ...

Predictive Analytics is a sophisticated forecasting system that relies on data mining, statistical modelling, and machine learning. It is an offshoot of advanced analytics that uses historical data to ...

Imagine a future where quantum computers supercharge machine learning—training models in seconds, extracting insights from ...

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...

Humans and most other animals are known to be strongly driven by expected rewards or adverse consequences. The process of ...

Future events such as the weather or satellite trajectories are computed in tiny time steps, so the computation must be both ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter ...