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 a mass-spring system using Python in this step-by-step tutorial! 🐍📊 Explore how to simulate oscillations, visualize motion, and analyze energy in a spring-mass system with code ...

Explore Python Physics Lesson 19 and learn how the Monte Carlo method can approximate Pi with simple yet powerful simulations. In this lesson, we break down the Monte Carlo technique step by step, ...

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 ...

Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...