CS115 Final Report

To start the slide show, run the following command:

npm install

npm run dev

This will open the slide show in your default browser.

Project Description

This project is a study of the SVM algorithm and its application in the field of machine learning. We will be using the SVM algorithm to classify the EMNIST Dataset. The EMNIST Dataset is a set of handwritten characters that are used to train machine learning models to recognize handwritten characters. The SVM algorithm is a supervised learning algorithm that is used to classify data into different categories. We will be using the SVM algorithm to classify the EMNIST Dataset into different categories of handwritten characters.

This project implement the ByClass subset of the EMNIST Dataset. The ByClass subset contains 814,255 characters divided into 62 classes. Each class represents a different character. The characters are divided into uppercase and lowercase letters, as well as numbers. We perform preprocessing on the data to prepare it for training.

The preprocessed data is then used to train three models: SVM model, KNN model, CNN model.

For each model, we applied fine-tuning to optimize the hyperparameters. We then evaluated the performance of each model using the test set. We compared the performance of the three models and analyzed the results.

For more details, please refer to the slide show.

Contributors ✨

Thanks goes to these wonderful people (emoji key):

Le Kiet 💻 📖 🔣 🔬

This project follows the all-contributors specification. Contributions of any kind welcome!