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 ...
Read more
No More Tableau Downtime: Metadata API for Proactive Data Health
In today’s world, the reliability of data solutions is everything. When we build dashboards and reports, one expects that the ...
Read more
Mastering Hadoop, Part 3: Hadoop Ecosystem: Get the most out of your cluster
As we have already seen with the basic components (Part 1, Part 2), the Hadoop ecosystem is constantly evolving and ...
Read more
