Why is shuffling the data important when working with the MNIST dataset in deep learning?
Sunday, 13 August 2023
by EITCA Academy
Shuffling the data is an essential step when working with the MNIST dataset in deep learning. The MNIST dataset is a widely used benchmark dataset in the field of computer vision and machine learning. It consists of a large collection of handwritten digit images, with corresponding labels indicating the digit represented in each image. The
- Published in Artificial Intelligence, EITC/AI/DLPP Deep Learning with Python and PyTorch, Data, Datasets, Examination review
Tagged under:
Artificial Intelligence, Deep Learning, Generalization, MNIST Dataset, Overfitting, Shuffling Data
What is the purpose of shuffling the sequential data list after creating the sequences and labels?
Sunday, 13 August 2023
by EITCA Academy
Shuffling the sequential data list after creating the sequences and labels serves a crucial purpose in the field of artificial intelligence, particularly in the context of deep learning with Python, TensorFlow, and Keras in the domain of recurrent neural networks (RNNs). This practice is specifically relevant when dealing with tasks such as normalizing and creating