Tech Xplore

Pinpointing direction in noisy 2D data: New algorithm could improve imaging, AI, particle research and more

A University of Hawaiʻi at Mānoa student-led team has developed a new algorithm to help scientists determine direction in ...
Tech Xplore

Physics-aware AI algorithm uses Newton's third law to keep simulations stable

A team of EPFL researchers has developed an AI algorithm that can model complex dynamical processes while taking into account ...
TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
IEEE

K-Nearest Neighbor Algorithm Based on the Framework of Ordered Pair of Normalized Real Numbers

Abstract: The K-nearest neighbors (kNNs) algorithm, a cornerstone of supervised learning, relies on similarity measures constrained by real-number-based distance metrics. A critical limitation of ...
CU Boulder News & Events

Machine Learning Updates - MS-CS, MS-AI on Coursera

We are excited to inform you that the current Machine Learning: Theory and Hands-On Practice with Python Specialization (taught by Professor Geena Kim) is being retired and will be replaced with a new ...
tech2geek

Scikit-learn: The Essential Machine Learning Library for Python

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...
techannouncer

Unlocking Machine Learning Potential with Google Colab Python

Google Colab is a really handy tool for anyone working with machine learning and data stuff. It’s free, it runs in the cloud, and it lets you use Python without a lot of fuss. Whether you’re just ...
BMJ

Prediction of zero-dose children using supervised machine learning algorithm in Tanzania: evidence from the recent 2022 Tanzania Demographic and Health Survey

Objectives This study aimed to employ machine learning algorithms to predict the factors contributing to zero-dose children in Tanzania, using the most recent nationally representative data. Design ...
labs.sogeti

MACHINE LEARNING ALGORITHMS FOR TEST AUTOMATION

The emergence of using Machine Learning Techniques in software testing started in the 2000s with the rise of Model-Based Testing and early bug prediction models trained on historical defect data. It ...