Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...

For most of my life, I've been a console gamer. From the moment I got a Nintendo Entertainment System (NES) as a combination birthday and Christmas present at the tail end of 1986, I became absolutely ...

A new post on Apple’s Machine Learning Research blog shows how much the M5 Apple silicon improved over the M4 when it comes to running a local LLM. Here are the details. A couple of years ago, Apple ...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...

The University Research Computing Facility (URCF) is pleased to announce our Fall 2025 workshop series, which will run from November 11 - November 20. These workshops will teach the fundamentals of ...

If there is one skill that sits at the heart of most successful AI and machine learning projects today, it is Python. Whether a company wants to build smarter automation, design predictive solutions, ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...

Abstract: sQUlearn introduces a user-friendly, noisy intermediate-scale quantum (NISQ)-ready Python library for quantum machine learning (QML), designed for seamless integration with classical machine ...

Join the University Libraries for our new Introduction to Python workshop series with Genevieve Milliken, data librarian, on September 18 and 25. This beginner-friendly, two-part workshop introduces ...