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Happy-Sad-Image-Classification

Image Classification model used deep learning for classifying a person happy or sad from any given image. I achieved almost 100% accuracy. This project is encapsulated in a Jupyter notebook and serves as an introduction to fundamental operations, library usage, and system configurations. It is structured to guide you through the initial setup, including library imports and optional configurations for enhanced performance, especially when working with GPUs.

Setup and Installation

Begin by ensuring all the necessary dependencies are installed. Then, proceed to launch the notebook in your preferred environment that supports Jupyter notebooks, such as JupyterLab or the classic Jupyter Notebook interface.

Usage

Navigate through the notebook by running the cells in order. The content is structured to sequentially introduce concepts and operations. If your system includes a GPU, you may find the optional GPU memory management section particularly useful for optimizing performance.

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Image Classification model used deep learning for classifying a person happy or sad from any given image. I achieved almost 100% accuracy. t

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