Abstract: For many years, topological data analysis (TDA) and deep learning (DL) have been considered separate data analysis and representation learning approaches, which have nothing in common. The ...

This article adopts a constructivist grounded theory approach based on the principle of intersubjective relations and the co-construction of interpretations. Reflecting on the author's experiences as ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

We introduce LAMBDA, a novel open-source, code-free multi-agent data analysis system that harnesses the power of large models. LAMBDA is designed to address data analysis challenges in complex ...

If you’d like an LLM to act more like a partner than a tool, Databot is an experimental alternative to querychat that also works in both R and Python. Databot is designed to analyze data you’ve ...

What if you could transform the way you analyze data in just 12 minutes? Picture this: a mountain of raw numbers and spreadsheets that once felt overwhelming now becomes a treasure trove of actionable ...

The volume of data generated by logs and incident alerts is nothing short of overwhelming. But for security operations teams, sifting through it to identify and mitigate potential threats makes the ...

Abstract: With the rapid development of big data and artificial intelligence technologies, the scale and complexity of financial data continue to increase, and traditional analysis methods can no ...

The analysis of multi-environment trials (MET) data in plant breeding and agricultural research is inherently challenging, with conventional ANOVA-based methods exhibiting limitations as the ...