Obedience Corp Website

Principles Of AI Lab Exercises

PROJECT 02: LOGIC - The purpose of this project is to design and implement a logical search agent for a partially observable environment. This will be accomplished by implementing an agent that navigates through the Wumpus World.

Pocket-Lab is a set of automations to create a self-hosted AI lab with your own LLM backend and support services.

Universal AI lab provisioning for Ubuntu 24.04 — Docker, Ollama, Qdrant, Python, Dify, Flowise, n8n, Langfuse, Traefik. Any cloud or bare metal.

This is a repo comprising of S5 AI and ML lab Programs. Programs are designed for educational purposes and demonstrate AI and ML concepts.

Foo-Voodoo on All Things AI @dev2deploy

Swift port of Gliner2 framework

Tactical AI tools for modern workflows.

AI Lab: Prototipo de catálogo digital de productos para Detalles Angelito.

🔍 Detect fraudulent credit card transactions in real time with an advanced machine learning system featuring a web dashboard and mobile support.

Lab 'Natural ou Fake Natty? Como Vencer na Era das IAs Generativas!'

In prolog, We declare some facts. These facts constitute the Knowledge Base of the system. We can query against the Knowledge Base. We get output as affirmative if our query is already in the knowledge Base or it is implied by Knowledge Base, otherwise we get output as negative.

PROJECT 01: SEARCH - Suggest or implement learned algorithms to assist Pac-Man in finding food without getting killed by monsters

run llms and slms on your hardware & browser

Solving real world problems with AI. Done under Lab of Artificial Intelligence in 2022-2023

This repository aims at keeping a record of our lab work as a part of Artificial Intelligence course during the 6th semester. This repository contains the code for the various problems and the document description submitted for each experiment.

SRMIST Kattankulathur Artificial Intelligence-18CSC305J lab exercises implemented in python

AI lab implementations covering informed and uninformed search algorithms with classic problem-solving examples in PythonAI Repository

Credit card fraud is a significant problem, with billions of dollars lost each year. Machine learning can be used to detect credit card fraud by identifying patterns that are indicative of fraudulent transactions. Credit card fraud refers to the physical loss of a credit card or the loss of sensitive credit card information.