From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with ...
Background While the incidence of hospital adverse events appeared to be declining before 2019, the COVID-19 pandemic may ...
Abstract: In today’s digital era, where information flows seamlessly and is readily available and accessible. However, these information and communication systems are highly dependent on the ...
ABSTRACT: Nowadays, understanding and predicting revenue trends is highly competitive, in the food and beverage industry. It can be difficult to determine which aspects of everyday operations have the ...
ABSTRACT: Nowadays, understanding and predicting revenue trends is highly competitive, in the food and beverage industry. It can be difficult to determine which aspects of everyday operations have the ...
Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...
This repository contains example code for the machine learning course by Andrew Ng. The code focuses on implementing and understanding core machine learning concepts using Python 🐍.
Abstract: Machine learning models for continuous outcomes often yield systematically biased predictions, particularly for values that largely deviate from the mean. Specifically, predictions for large ...
Sequences are a universal abstraction for representing and processing information, making sequence modeling central to modern deep learning. By framing computational tasks as transformations between ...
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