Data Science and Machine Learning (Theory and Projects) A to Z - DNN and Deep Learning Basics: DNN PyTorch CIFAR10 Examp

The video tutorial demonstrates how to implement a deep neural network using PyTorch on the CIFAR-10 dataset. It covers importing necessary packages, downloading and exploring the dataset, transforming data into tensors, and batching it. The tutorial then defines a neural network model, sets up a training routine with an optimizer and scheduler, and finally runs validation and testing to evaluate accuracy. The tutorial emphasizes the importance of using appropriate schedulers and optimizers for efficient training.

What optimizer is used in the training routine?

What is the purpose of the learning rate scheduler?

What is the accuracy calculation method mentioned for validation?

What type of neural networks are suggested for images?