What is MNIST Dataset?
The MINST dataset stands for “Modified National Institute of Standards and Technology“. The dataset contains a large collection of handwritten digits that is commonly used for training various image processing systems. The dataset was created by re-mixing samples from NIST’s original datasets, which were taken from American Census Bureau employees and high school students. It is designed to help scientists develop and test machine learning algorithms in pattern recognition and machine learning. It contains 60,000 training images and 10,000 testing images, each of which is a grayscale image of size 28×28 pixels.
MNIST Dataset : Practical Applications Using Keras and PyTorch
The MNIST dataset is a popular dataset used for training and testing in the field of machine learning for handwritten digit recognition. The article aims to explore the MNIST dataset, its characteristics and its significance in machine learning.
Table of Content
- What is MNIST Dataset?
- Structure of MNIST dataset
- Origin of the MNIST Dataset
- Methods to load MNIST dataset in Python
- Loading MNIST dataset using TensorFlow/Keras
- Loading MNIST dataset Using PyTorch
- Significance of MNIST in Machine Learning
- Applications of MNIST