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This is the second in a multi-part series on creating web applications with generative AI integration. Part 1 focused on explaining the AI stack and why the application layer is the best place in the stack to be. Check it out here. Table of Contents Introduction I thought spas were supposed to be relaxing? Microservices are […]

When working in Data Science, it is not uncommon to encounter problems with competing objectives. Whether designing products, tuning algorithms or optimizing portfolios, we often need to balance several metrics to get the best possible outcome. Sometimes, maximizing one metrics comes at the expense of another, making it hard to have an overall optimized solution.

Scientific publication T. M. Lange, M. Gültas, A. O. Schmitt & F. Heinrich (2025). optRF: Optimising random forest stability by determining the optimal number of trees. BMC bioinformatics, 26(1), 95. Follow this LINK to the original publication. Random Forest — A Powerful Tool for Anyone Working With Data What is Random Forest? Have you ever

This post will share how to build an AI journal with the LlamaIndex. We will cover one essential function of this AI journal: asking for advice. We will start with the most basic implementation and iterate from there. We can see significant improvements for this function when we apply design patterns like Agentic Rag and

In the beginning, building Machine Learning models was a skill only data scientists with knowledge of Python could master. However, low-code AI platforms have made things much easier now. Anyone can now directly make a model, link it to data, and publish it as a web service with just a few clicks. Marketers can now

Introduction In the first post of this series (Agentic AI 101: Starting Your Journey Building AI Agents), we talked about the fundamentals of creating AI Agents and introduced concepts like reasoning, memory, and tools. Of course, that first post touched only the surface of this new area of the data industry. There is so much

AlphaEvolve imagined as a genetic algorithm coupled to a large language model. Picture created by the author using various tools including Dall-E3 via ChatGPT. Large Language Models have undeniably revolutionized how many of us approach coding, but they’re often more like a super-powered intern than a seasoned architect. Errors, bugs and hallucinations happen all the

Decision trees are a popular supervised learning algorithm with benefits that include being able to be used for both regression and classification as well as being easy to interpret. However, decision trees aren’t the most performant algorithm and are prone to overfitting due to small variations in the training data. This can result in a