Explore the latest AI news and research tagged #machine learning — curated from top sources including OpenAI, Anthropic, Google DeepMind, and more.
The latest set of open-source models from DeepSeek are here. While the industry anticipated the dominance of “closed” iterations like GPT-5.5, the arrival of DeepSeek-V4 has ticked the dominance in…
More variables don't make a better scoring model. Stable variables do. Here's how to find them. The post How to Select Variables Robustly in a Scoring Model appeared first on…
The silent gaps in synthetic data that only show up when your model is already in production. The post Your Synthetic Data Passed Every Test and Still Broke Your Model…
It’s simpler than you think. The post Lasso Regression: Why the Solution Lives on a Diamond appeared first on Towards Data Science .
Last Updated on April 23, 2026 by Editorial Team Author(s): CapeStart Originally published on Towards AI. Nowadays, in the enterprise environment, information is dispersed across CRMs, ERPs, databases, and millions…
Learn how Propensity Score Matching uncovers true causality in observational data. By finding "statistical twins," we eliminate selection bias to reveal the real impact of your interventions and business decisions.…
How I turned LLM persona interviews into a repeatable customer research workflow The post Claude Code Skills: The Sweet Spot Between Prompts and Python Libraries appeared first on Towards Data…
FastAPI has become one of the most popular ways to serve machine learning models because it is lightweight, fast, and easy to use.
Last Updated on April 23, 2026 by Editorial Team Author(s): DrSwarnenduAI Originally published on Towards AI. GPT-4 Has 1.8 Trillion Parameters. It Uses 2% of Them Per Token. DeepSeek-R1: 671…
How you can build your own Thompson Sampling Algorithm object in Python and apply it to a hypothetical yet real-life example The post DIY AI & ML: Solving The Multi-Armed…
The alliance targets data gaps in robotics, with Amazon eyeing fulfillment center deployments.
Apple is presenting new research at the annual International Conference on Learning Representations (ICLR) , which takes place in person in Rio de Janeiro, Brazil, from April 23 to 27.…
You've probably written a decorator or two in your Python career.
Last Updated on April 17, 2026 by Editorial Team Author(s): Raj kumar Originally published on Towards AI. When financial analysts need to segment customer profitability across product lines and regions,…
Last Updated on April 16, 2026 by Editorial Team Author(s): Hossein Chegini Originally published on Towards AI. “A 100-Queen solution” …picture from ‘repo/images/solutions’ Code Investigation In the previous introduction, I…
Last Updated on April 16, 2026 by Editorial Team Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, Anthropic…
Last Updated on April 16, 2026 by Editorial Team Author(s): Raj kumar Originally published on Towards AI. Part 4 of a 4-part series: From Data to Decisions Most machine learning…
Last Updated on April 13, 2026 by Editorial Team Author(s): idibaliban75 Originally published on Towards AI. Introduction Digital document creation has evolved from a manual, design‑heavy process into a workflow…
Last Updated on April 13, 2026 by Editorial Team Author(s): Gaurav Yadav Originally published on Towards AI. Anthropic shipped Managed Agents this week. AWS Bedrock AgentCore has been GA for…
Last Updated on April 10, 2026 by Editorial Team Author(s): Utkarsh Mittal Originally published on Towards AI. A complete, step-by-step walkthrough of how gradient descent works with absolute-value loss —…
Last Updated on April 10, 2026 by Editorial Team Author(s): Yusuf Ismail Originally published on Towards AI. Picture this. It’s 2 am. You’re on a trolley in a hospital corridor.…
What is the Role of Mathematics in Modern Machine Learning? The past decade has witnessed a shift in how progress is made in machine learning. Research involving carefully designed and…
How AI hype leads to flawed research that fuels more hype
Have you ever trained a model you thought was good, but then it failed miserably when applied to real world data? If so, you’re in good company.