These open-source MMM tools solve different measurement problems, from budget optimization to forecasting and preprocessing.

This study proposes an important new approach to analyzing cell-count data, which are often undersampled and cannot be accurately assessed using traditional statistical methods. The case studies ...

pandas is the premier library for data analysis in Python. Here are some advanced things I like to do with pandas DataFrames to take my analysis to the next level. Change the index of a DataFrame On a ...

Abstract: This paper describes a novel brain and cellular data analysis. Bayesian reasoning and hierarchical models provide important information. Bayesian principles continually anticipate model ...

Bloomberg’s BQuant analytics platform has been named Best AI Solution for Historical Data Analysis in the A-Team Group’s inaugural AI in Capital Markets Awards 2025. This award category recognizes the ...

Abstract: Tensor factorization-based data completion methods have found extensive application in cyber-physical-social systems (CPSS), particularly in intelligent transportation systems. However, most ...

This important study presents a meta-analysis confirming a statistically significant association between slow oscillation-spindle coupling and memory formation, although the reported effects are ...

This blog post and audio file is another in the series "Defending the Algorithm™" written and edited by Pittsburgh, Pennsylvania Business, IP and AI Trial Lawyer Henry M. Sneath, Esq. and was authored ...

What is Data Science Fundamentals with Python? Data science transforms information into action. Through programming, analytics, and machine learning, data professionals uncover patterns, generate ...

Synthetic dataset outputs for public analysis without privacy risk. Part of my current workflow as survey leader of the Data Engineering Pilipinas group. Comparable distributions per column: based on ...