kavishc18 / classification-of-mnist-dataset Goto Github PK

This GitHub repository serves as a comprehensive guide for classifying handwritten digits from the MNIST dataset. We explore a variety of machine learning techniques, including but not limited to Support Vector Machines (SVMs), Random Forests, and Naive Bayes, to assess their performance and accuracy in this classic problem in computer vision and machine learning. The repository provides Jupyter notebooks for each algorithm, making it easy to understand the code, methodology, and results. We aim to furnish a one-stop resource for both beginners and experts interested in understanding the nuances of MNIST digit classification across multiple algorithms.