We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

Fraud detection is defined by a structural imbalance that has long challenged data-driven systems. Fraudulent transactions typically account for a fraction of a percent of total transaction volume, ...

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

The shift from volume to value requires more than enthusiasm. It requires engineering discipline, business ownership and the ...

A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an ...

Nigeria faces enormous public service challenges from traffic congestion in high urbanised areas to insecurity, healthcare delays, and inconsistent public planning. But with the right use of ...

People and institutions are grappling with the consequences of AI-written text. Teachers want to know whether students' work ...

Despite advanced algorithms and automation, one truth remains: Effective cybersecurity requires a careful balance between machine precision and human judgment.

Overview: Cloud computing startups in 2025 are pushing boundaries with AI integration, automation, and developer-centric services.Many are building tools to opt ...

The BCTVNet neural network provides accurate and rapid target volume delineation for cervical cancer brachytherapy ...

Multimodal Learning, Deep Learning, Financial Statement Analysis, LSTM, FinBERT, Financial Text Mining, Automated Interpretation, Financial Analytics Share and Cite: Wandwi, G. and Mbekomize, C. (2025 ...

What impressed judges was not only the sophistication of the underlying models, but also Bloomberg’s consistent demonstration ...