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 ...
The U.S. healthcare system generates massive volumes of data spanning patients, treatments, and billing but real datasets are often inaccessible due to privacy laws like HIPAA. This project was ...
Apple has released Pico-Banana-400K, a highly curated 400,000-image research dataset which, interestingly, was built using Google’s Gemini-2.5 models. Here are the details. Apple’s research team has ...
What if you could turn Excel into a powerhouse for advanced data analysis and automation in just a few clicks? Imagine effortlessly cleaning messy datasets, running complex calculations, or generating ...
Introduction: Integrating immune repertoire sequencing data with single cell sequencing data offers profound insights into the diversity of immune cells and their dynamic changes across various ...
In this tutorial, we demonstrate how to efficiently fine-tune the Llama-2 7B Chat model for Python code generation using advanced techniques such as QLoRA, gradient checkpointing, and supervised ...
Abstract: This work aims to compare two different Feature Extraction Algorithms (FEAs) viz. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), using a K-Nearest Neighbor (KNN) ...
ABSTRACT: The integration of artificial intelligence into the development and production of mechatronic products offers a substantial opportunity to enhance efficiency, adaptability, and system ...
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