Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...

Each Python version enhances execution speed, memory management, and runtime efficiency. For example, Python 3.12 introduced measurable speed gains (up to 5–10% faster for certain workloads) compared ...

Over the past week, I’ve been exploring one of the most classic — yet powerful — business analytics techniques: Market Basket Analysis. The goal was simple but impactful — to understand how products ...

Version 8.0 has been released. Get it here or with Docker. This release adds the capability to use pre-trained scikit-learn, Keras or REST API based models with Qlik. More on this here. Qlik's ...

Development of a novel deep learning architecture to accurately predict user preferences based on their viewing behavior and patterns. Integration of graph analysis techniques with deep learning to ...

The operation of the power grid is closely related to meteorological disasters. Changes in meteorological conditions may have an impact on the operation and stability of the power system, leading to ...

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...

The exploration of important biomarkers associated with cancer development is crucial for diagnosing cancer, designing therapeutic interventions, and predicting prognoses. The analysis of gene ...

Apriori and FP-Growth are two fundamental algorithms used for frequent itemset mining in market basket analysis. Understanding consumer behaviour is crucial for providers to enhance marketing ...

Quantifying synergistic environmental effects in water contamination is still an open issue. Here, we have analyzed geolocalized data of pollutants recorded in 2018 in surface and groundwater of ...