Karunesh UpadhyayLearning Rate SchedulersIn the realm of deep learning, finding the right learning rate is often a complicated task. Too high, and your model might diverge…Jun 30Jun 30
Karunesh UpadhyayContainers-PytorchIn PyTorch, containers are classes or data structures designed to hold and organize neural network components such as layers, modules…Nov 7, 2023Nov 7, 2023
Karunesh UpadhyayImplement MobileNet-v1 in PyTorchMobileNet is a convolutional neural network architecture that is specifically designed for efficient use on mobile and embedded devices. In…Oct 3, 20231Oct 3, 20231
Karunesh UpadhyayImplement Inception-v1 in PyTorchIn the world of deep learning and computer vision, Inception-v1, known as GoogleNet, stands as a landmark in innovation and efficiency. In…Oct 3, 2023Oct 3, 2023
Karunesh UpadhyayImplement DenseNet in PyTorchIn this article, we dive into the world of deep learning by building the DenseNet architecture from scratch. Without relying on…Oct 2, 2023Oct 2, 2023