ABOUT THIS FEED
KDnuggets is one of the most widely read online platforms dedicated to data science, machine learning, artificial intelligence, and analytics. Founded in the late 1990s by Gregory Piatetsky-Shapiro, it has grown into a go-to hub for professionals, researchers, and enthusiasts who want to keep up with the latest trends, tutorials, tools, and career advice in the AI/ML ecosystem.
- From Spaghetti Code to Clean Python: A Beginner’s Guide
Learn how to refactor messy Python code into clean, maintainable functions.
- 5 Python Techniques for Efficient Resource Orchestration
This article explains 5 Python techniques for efficient resource orchestration and sticks to what's stable today, 3.11 and later for the core techniques, with one 3.14-specific tool called out explicitly as requiring that version
- A Candid Abacus AI Review: The All-in-One AI Platform for Professionals & Enterprises
If you’re paying for ChatGPT, Claude, and another AI tool simultaneously, this review is for you. It covers what an AI platform like Abacus AI actually includes, how the credit system works in practice, and whether it genuinely replaces your current stack or just adds to it.
- Feature Engineering in Scikit-Learn: A KDnuggets Cheat Sheet
Once feature engineering lives inside a Pipeline, each step is fitted on training data only, and the model is scored what it actually earned. And that is the idea behind this new cheat sheet.
- 7 Steps to Become a Forward Deployed Engineer in 2026
FDEs are becoming some of the most in-demand engineers in AI. Here’s the 7-step roadmap to becoming one in 2026.
- 5 Useful Python Scripts to Automate CSV Processing
Automate common CSV tasks with these 5 Python scripts for cleaning, validating, transforming, and processing CSV files using the standard library.
- Build an AI Data Analyst That Thinks Like a Senior Analyst
A six-stage pipeline that checks its numbers before calling anything an answer.
- 7 Approaches to Efficient LLM Training on Limited Hardware
Learn seven engineering techniques to train large language models on consumer GPUs without running out of memory.
- From RAG to Agentic AI: Building the Next Generation of Intelligent Enterprise Systems
Over the past several years, I have worked through three successive generations of intelligent retrieval systems, each solving problems the previous generation could not. Here is what I have learned.
- Is ArrowJS Really the UI for the Agentic Era? Here’s What I Found
The way we build interfaces is changing. As AI agents write more of our code, the tools we use to render that code may need to change too.