Category: Data Science

Author: KDnuggets So, what is big tech’s influence on ai development? It is both transformative and concerning. Go to Source

Author: Matthew Mayo In this article, we look at five revelations from the paper “Why Do Language Models Hallucinate?” Go to Source

Author: Bala Priya C A quick look at 7 Python libraries that help analytics engineers clean, transform, and analyze data effectively. Go to Source

Author: Nate Rosidi Generate synthetic data and build a machine learning portfolio project with AI. Go to Source

Author: /u/AutoModerator Welcome to this week’s entering & transitioning thread! This thread is for any questions about getting started, studying, or transitioning into the data […] Read More

Author: Bala Priya C Polars is a lightning-fast DataFrame library, perfect for quick, scalable data analysis. This guide covers the basics to get you started. […] Read More

Author: Jayita Gulati Let’s take a look at how vLLM streamlines the process of serving large language models by making it faster and easier to […] Read More

Author: Iván Palomares Carrascosa How to build an orchestration workflow to prototype a RAG system that uses Airtable text databases as the knowledge base for […] Read More

Author: KDnuggets To turn AI from pilots into impact: define the problem, fix your data, upskill people, start small and scale, and bake in responsible […] Read More

Author: Natassha Selvaraj A step-by-step guide to building a Model Context Protocol (MCP) for your data science team (and why adapting AI is the key […] Read More