Dive deep into Nesterov Accelerated Gradient (NAG) and learn how to implement it from scratch in Python. Perfect for improving optimization techniques in machine learning! 💡🔧 #NesterovGradient #Mach ...

Learn how to implement the Nadam optimizer from scratch in Python. This tutorial walks you through the math behind Nadam, ...

So far, running LLMs has required a large amount of computing resources, mainly GPUs. Running locally, a simple prompt with a typical LLM takes on an average Mac ...

JSON Prompting is a technique for structuring instructions to AI models using the JavaScript Object Notation (JSON) format, making prompts clear, explicit, and machine-readable. Unlike traditional ...

What if you could create your very own personal AI assistant—one that could research, analyze, and even interact with tools—all from scratch? It might sound like a task reserved for seasoned ...

This repository provides a Python client library and a detailed tutorial for interacting with the Open WebUI REST API. It is designed to be a simple, yet powerful, starting point for developers ...

Abstract: Simulation is an excellent tool to study real-life systems with uncertainty. Discrete-event simulation (DES) is a common simulation approach to model time-dependent and complex systems.

This tutorial will guide you through the process of using SQL databases with Python, focusing on MySQL as the database management system. You will learn how to set up your environment, connect to a ...

An experimental ‘no-GIL’ build mode in Python 3.13 disables the Global Interpreter Lock to enable true parallel execution in Python. Here’s where to start. The single biggest new feature in Python ...

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