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.
- How to Use Hugging Face Spaces to Host Your Portfolio for Free
Hugging Face Spaces is a free way to host a portfolio with live demos, and this article walks through setting one up step by step.
- 7 Scikit-learn Tricks for Hyperparameter Tuning
Ready to learn these 7 Scikit-learn tricks that will take your machine learning models' hyperparameter tuning skills to the next level?
- This Is How Successful Data Teams Are Using AI (Sponsored)
Successful data teams aren’t using more AI; they’re using AI differently. They embed it into workflows and decisions, employing ownership models that many SMBs haven’t adopted.
- Top 7 Coding Plans for Vibe Coding
API bills are killing vibe coding. These seven coding plans let you ship faster without watching token costs.
- The Multimodal AI Guide: Vision, Voice, Text, and Beyond
AI systems now see images, hear speech, and process video, understanding information in its native form.
- 3 Ways to Anonymize and Protect User Data in Your ML Pipeline
In this article, you will learn three practical ways to protect user data in real-world ML pipelines, with techniques that data scientists can implement directly in their workflows.
- 7 Under-the-Radar Python Libraries for Scalable Feature Engineering
This article lists 7 under-the-radar Python libraries that push the boundaries of feature engineering processes at scale.
- The KDnuggets ComfyUI Crash Course
This crash course will take you from a complete beginner to a confident ComfyUI user, walking you through every essential concept, feature, and practical example you need to master this powerful tool.
- 5 Useful DIY Python Functions for Parsing Dates and Times
Dates and times shouldn’t break your code, but they often do. These five DIY Python functions help turn real-world dates and times into clean, usable data.
- Integrating Rust and Python for Data Science
Python remains at the forefront data science, it is still very popular and useful till date. But on the other hand strengthens the foundation underneath. It becomes necessary where performance, memory control, and predictability become important.