Data Augmentation, Regularization, and ResNets | Deep Learning with PyTorch: Zero to GANs | 5 of 6

“Deep Learning with PyTorch: Zero to GANs” is a beginner-friendly online course offering a practical and coding-focused introduction to deep learning using the PyTorch framework. Learn more and register for a certificate of accomplishment here: http://zerotogans.com Watch the entire series here: https://www.youtube.com/playlist?list=PLWKjhJtqVAbm5dir5TLEy2aZQMG7cHEZp Code and Resources: 🔗 Classifying CIFAR10 images using ResNet and Regularization techniques in PyTorch: https://jovian.ai/aakashns/05b-cifar10-resnet 🔗 Image Classification using Convolutional Neural Networks in PyTorch: https://jovian.ai/aakashns/05-cifar10-cnn 🔗 Discussion forum: https://jovian.ai/forum/t/lecture-5-data-augmentation-regularization-and-resnets/13772 Topics covered in this video: * Improving the dataset using data normalization and data augmentation * Improving the model using residual connections and batch normalization * Improving the training loop using learning rate annealing, weight decay, and gradient clip * Training a state of the art image classifier from scratch in 10 minutes This course is taught by Aakash N S, co-founder & CEO of Jovian - a data science platform and global community. - YouTube: https://youtube.com/jovianml - Twitter: https://twitter.com/jovianml - LinkedIn: https://linkedin.com/company/jovianml -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news