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announced Structured Outputs for its top models in its API, a brand new feature designed to be sure that model-generated outputs exactly match the JSON Schemas provided by developers.  This solves an issue many...

If with Python for data, you may have probably experienced the frustration of waiting minutes for a Pandas operation to complete. At first, the whole lot seems high quality, but as your dataset grows...

Show code library(tibble) library(ggplot2) library(dplyr) library(tidyr) library(latex2exp) library(scales) library(knitr) Over the past few years working in marketing measurement, I’ve noticed that is one of the vital poorly understood testing and measurement topics. Sometimes it’s misunderstood and sometimes it’s not applied in...

exploring features within the OpenAI Agents SDK framework, there’s one capability that deserves a better look: input and output guardrails. In previous articles, we built our first agent with an API-calling tool after which...

: You will have built a fancy LLM application that responds to user queries about a selected domain. You will have spent days organising the entire pipeline, from refining your prompts to adding context...

Context Engineering by now. This text will cover the important thing ideas behind creating LLM applications using Context Engineering principles, visually explain these workflows, and share code snippets that apply these concepts practically. Don’t...

is a game changer in Machine Learning. In actual fact, within the recent history of Deep Learning, the thought of allowing models to deal with probably the most relevant parts of an input...

The code of this text could be found on this GitHub folder.One of my favorite professors throughout my studies told me this:“Simply because your algorithm is inefficient, it doesn’t mean that the issue is...