Implementation of the Double Deep Q-Learning algorithm with a prioritized experience replay memory to train an agent to play the minichess variante Gardner Chess

Solutions for the Projects of the Artificial Intelligence (CS 188) course of UC Berkeley

Discord bot powered by artificial intelligence with memory capabilities and ability to execute terminal commands.

UPT-Artist is a Python application that utilizes OpenAI's GPT-3.5 language model to generate logos and images based on user input. It allows users to select the type of logo they want and provide a prompt for image generation. The application processes the data locally, ensuring data security, and generates a logo image using the OpenAI API.

Projects Implemented for the AI Product Manager Nanodegree Program

A personal assistant application named Alexa that performs various tasks through voice commands. Features include weather updates, web searches, news headlines, Wikipedia summaries, jokes, and more. Easily customizable and extendable with new functionalities.

Projects Implemented for the Udacity Natural Language Processing Engineer Nanodegree Program

Explore foundational AI concepts through the Pac-Man projects, designed for UC Berkeley's CS 188 course. Implement search algorithms, multi-agent strategies, and reinforcement learning techniques in Python, emphasizing real-world applications. Engage in the Eutopia Pac-Man contest for a multiplayer capture-the-flag challenge

AI Tool for quick Data Analysis, Visualisation and model development but much more smarter and secure than Code Interpreter.

Application made using Flask that runs on a ML Model trained using random forest classification model that helps in prediction of heart disease

This project uses a pre-trained ResNet50 model from the FastAI library to detect pneumonia in chest X-rays. The dataset which is available on kaggle is used for training the model which classifies the chest xray as NORMAL, VIRAL or BACTERIAL and this project is deployed on Flask

A game of connect four with an AI to play against.

🛣 Building an end-to-end Promptable Semantic Segmentation (Computer Vision) project from training to inferencing a model on LandCover.ai data (Satellite Imagery).