This is an open collection of methodologies, tools and step by step instructions to help with successful training and fine-tuning of large language models and multi-modal models and their inference.
Learn how to model 1D motion in Python using loops! 🐍⚙️ This step-by-step tutorial shows you how to simulate position, velocity, and acceleration over time with easy-to-follow Python code. Perfect ...
This framework provides a comprehensive set of tools and utilities for implementing and experimenting with Extreme Learning Machines using Python and TensorFlow. ELMs are a type of machine learning ...
Abstract: Machine learning is widely used to solve networking challenges, ranging from traffic classification and anomaly detection to network configuration. However, machine learning also requires ...
Researchers have published the recipe for an artificial-intelligence model that reviews the scientific literature better than ...
Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...