Discover what counterfactual explanations are and how illustrating changes that lead to different model outcomes enhances transparency, fairness, and actionable decision-making in machine learning.
Integrating causal inference into Marketing Mix Models transforms correlation-based marketing analytics into powerful decision engines that reveal the true impact of campaigns.
Delving into the R&D journey of creating a pioneering Text-to-SQL tool, exploring the intersection of data governance, business language challenges, and the semantic power of LLMs.
An exploration of current limitations in Large Language Models (LLM) through concrete examples, revealing their surprising struggles with seemingly simple tasks.
At Ekimetrics, we've tackled the challenge of ensuring the relevance and accuracy of chatbot responses by developing a cutting-edge chatbot system designed to navigate the complex landscape of HR policies.
Bayesian neural networks (BNNs) is a pioneering approach that embraces uncertainty as a strength.
Understand why multimodal deep learning models are more accurate than assembled unimodal models.
Discover uncertainty quantification for time series forecasting.
Willing to learn about the online ad market, cross-media effects and contextual advertising? This article wraps up the content of a PhD thesis on the economics of online advertising, defended by Rémi Devaux, Senior Consultant at Ekimetrics.