Artificial Intelligence Project

This repository is dedicated to the development of various artificial intelligence systems and algorithms from scratch. The project is structured into several key components, focusing on building a comprehensive knowledge base approach and implementing machine learning techniques.

Project Structure

knowledgebase

This module focuses on the knowledge-based approach to AI, which includes rule-based systems, expert systems, and logical reasoning frameworks that utilize domain-specific knowledge to make decisions.

machinelearning

This module contains various submodules related to different machine learning paradigms:

llm (Large Language Models)

Includes implementations and adaptations of large language models with specifics versions:

• Meta-Llama-3-70B: Implementation of a 70B parameter model.
• Meta-Llama-3-70B-Instruct: Instruction-based variant of the 70B model.
• Meta-Llama-3-8B: Smaller 8B parameter model version.
• Meta-Llama-3-8B-Instruct: Instruction-based variant of the 8B model.

supervisedlearning

Focuses on classical supervised learning algorithms:

• linear-regression: Module for linear regression implementation.
• logistic-regression: Module for logistic regression techniques.
• neural-networks: Implements various forms of neural networks.

utilities

Contains general utility functions and scripts that support machine learning operations:

• activation_functions.py: Includes various activation functions used in neural networks.

Getting Started

To get started with this project, clone the repository and navigate into the respective directories to view the implementations.