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Tag: KDnuggets
3 Polars Tricks for High-Performance Data Manipulation
Almost every slow Polars script lacks in terms of one of these two: its expression engine written and executing in Rust across every core at its disposal,…
What’s So Good About ChatGPT Work? Here’s What I Found
This article walks through how ChatGPT Work specifically earns its reputation, where the underlying models genuinely hold up against the competition, and…
5 Free Zoomcamps From Data Pipelines to AI Agents
Explore five free hands-on workshops covering data engineering, machine learning, MLOps, LLMs, AI agents, and AI development through practical lessons,…
Reusing the Prompt Prefix with a Key-Value Cache for SLM Optimization
In this second article in our short series on SLM optimization techniques we focus on the reuse of the prompt prefix with a key-value cache.
5 Prompt Optimization Strategies That Actually Improve LLM Output
This article covers five prompt optimization strategies such as: prompt optimization, prompt engineering, LLM output quality, few-shot prompting,…
Estimators in Scikit-LLM: A KDnuggets Cheat Sheet
Scikit-LLM wraps language models in the scikit-learn estimator API, so it drops into a Pipeline or a cross-validation loop natively.
How to Build Effective Evals for AI Agents
Learn how to build effective evals for AI agents, from designing clear tasks and choosing the right graders to building reliable eval harnesses and…
What’s Actually Inside 24,723 Tokens of a Search Result? We Broke It Down, Field by Field
See how SerpApi’s Markdown output can cut search-result token usage by up to 74%, reducing AI agent costs and context-window overhead.
What’s So Good About ChatGPT Work? Here’s What I Found
This article walks through how ChatGPT Work specifically earns its reputation, where the underlying models genuinely hold up against the competition, and…