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:    • Deep Learning with PyTorch Course - Decemb...  

Code and Resources:
🔗 Classifying CIFAR10 images using ResNet and Regularization techniques in PyTorch: https://jovian.ai/aakashns/05b-cifar1...
🔗 Image Classification using Convolutional Neural Networks in PyTorch: https://jovian.ai/aakashns/05-cifar10...
🔗 Discussion forum: https://jovian.ai/forum/t/lecture-5-d...

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:    / jovianml  
Twitter:   / jovianml  
LinkedIn:   / jovianml  

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