Categories: AI/ML News

Machine learning algorithm enables faster, more accurate predictions on small tabular data sets

Filling gaps in data sets or identifying outliers—that’s the domain of the machine learning algorithm TabPFN, developed by a team led by Prof. Dr. Frank Hutter from the University of Freiburg. This artificial intelligence (AI) uses learning methods inspired by large language models. TabPFN learns causal relationships from synthetic data and is therefore more likely to make correct predictions than the standard algorithms that have been used up to now.

Data science vs. machine learning: What’s the difference?

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. This post will dive deeper into the nuances of each field. What is data science? Data science…

July 7, 2023

In "FAANG"

Machine learning masters massive data sets: Algorithm breaks the exabyte barrier

A machine-learning algorithm demonstrated the capability to process data that exceeds a computer's available memory by identifying a massive data set's key features and dividing them into manageable batches that don't choke computer hardware. Developed at Los Alamos National Laboratory, the algorithm set a world record for factorizing huge data…

September 12, 2023

In "AI/ML News"