How modern infostealers target macOS systems, leverage Python‑based stealers, and abuse trusted platforms and utilities to ...

This webinar introduced healthcare researchers to Bayesian meta-analysis methods, challenging the perception that these methods are inaccessible to non-statistical researchers. The session ...

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We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

Objective: Based on the Bayesian network, this study investigates the impact pathways of multidimensional factors related to the living environment—specifically housing factors, exposure to daily ...

ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...

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 ...

ABSTRACT: This study presents an integrated Multi-Criteria Decision-Making (MCDM) framework for sustainable landfill site selection in Chegutu Municipality, Zimbabwe. Combining the Analytical ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

I am running a Bayesian network analysis in JASP and have calculated the centrality measures (Expected Influence, Closeness and Betweenness). However, I would also like to obtain the confidence ...