csbanon / mnist-classifiers

A collection of Jupyter notebooks containing various MNIST digit and fashion item classification implementations using fully-connected and convolutional neural networks (CNNs) built with TensorFlow and Keras. 2020.

MNIST Classifiers

Overview

• Year: 2020
• Technologies: Python, NumPy, Matplotlib, TensorFlow, Keras
• Discipline(s): Computer Vision, Deep Learning
• Keywords: CNN, Classification, Computer Vision, Convolution, Convolutional Neural Network, Deep Learning, Fully-Connected, MNIST, Max-Pooling, Multi-Class Classification, Neural Network, 2-D Convolution, 2-D Max-Pooling

Description

This repository contains a collection of MNIST digit and fashion item classifiers built with fully-connected and convolutional neural networks (CNNs) using TensorFlow and Keras.

MNIST Digit Classifiers

• MNIST Digit Classification with a Fully-Connected Neural Network
• MNIST Digit Classification with a Convolutional Neural Network (CNN)

MNIST Fashion Item Classifiers

• MNIST Fashion Item Classification with a Fully-Connected Neural Network
• MNIST Fashion Item Classification with a Convolutional Neural Network (CNN)

For other notebooks with data science, machine learning, and computer vision implementations, check out my Notebooks repository. Thank you!