Skip to content Prescriptive Modeling Unpacked: A Complete Guide to Intervention With Bayesian Modeling.
In this article, I will demonstrate how to move from simply forecasting outcomes to actively intervening in systems to steer ...
Read more Building a Modern Dashboard with Python and Gradio
second in a short series on developing data dashboards using the latest Python-based GUI development tools, Streamlit, Gradio, and Taipy. ...
Read more Agentic RAG Applications: Company Knowledge Slack Agents
I that most companies would have built or implemented their own Rag agents by now. An AI knowledge agent can ...
Read more From Data to Stories: Code Agents for KPI Narratives
, we often need to investigate what’s going on with KPIs: whether we’re reacting to anomalies on our dashboards or ...
Read more Bayesian Optimization for Hyperparameter Tuning of Deep Learning Models
to tune hyperparamters of deep learning models (Keras Sequential model), in comparison with a traditional approach — Grid Search. Bayesian Optimization Bayesian ...
Read more Estimating Product-Level Price Elasticities Using Hierarchical Bayesian
In this article, I will introduce you to hierarchical Bayesian (HB) modelling, a flexible approach to automatically combine the results ...
Read more Multiple Linear Regression Analysis | Towards Data Science
full code for this example at the bottom of this post. Multiple regression is used when your response variable Y ...
Read more Understanding Random Forest using Python (scikit-learn)
trees are a popular supervised learning algorithm with benefits that include being able to be used for both regression and ...
Read more How to Set the Number of Trees in Random Forest
Scientific publication T. M. Lange, M. Gültas, A. O. Schmitt & F. Heinrich (2025). optRF: Optimising random forest stability by ...
Read more Google’s New AI System Outperforms Physicians in Complex Diagnoses
going to the doctor with a baffling set of symptoms. Getting the right diagnosis quickly is crucial, but sometimes even ...
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