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 ...

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 ...

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 ...

Overview: Structured online platforms provide clear, step-by-step learning paths for beginners.Real progress in data science comes from hands-on projects and co ...

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 ...

Artificial intelligence is now used in healthcare, banking, education, media, and public services. The demand for AI knowledge is increasing every year. YouTube has become one of the easiest platforms ...

Indian learning platform Entri has entered into a strategic partnership with Udemy to widen access to job-oriented digital skills training across multiple Indian languages, as demand for employability ...