🛣 Building an end-to-end Promptable Semantic Segmentation (Computer Vision) project from training to inferencing a model on LandCover.ai data (Satellite Imagery).
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Updated
Jun 20, 2023 - Jupyter Notebook
🛣 Building an end-to-end Promptable Semantic Segmentation (Computer Vision) project from training to inferencing a model on LandCover.ai data (Satellite Imagery).
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.
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.
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
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.
Application made using Flask that runs on a ML Model trained using random forest classification model that helps in prediction of heart disease
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