Data Augmentation, Regularization & ResNets | Deep Learning with PyTorch (5/6)

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Improving the dataset using data normalization and data augmentation, improving the model using residual connections and batch normalization, getting familiar with ResNets - all in one beginner-friendly tutorial. This lecture is part 5/6 of the Deep Learning with PyTorch Free Certification course. To learn more visit https://jovian.ai/learn/deep-learning...

Time Breaks:
00:00 Introduction

Code and Resources:
🔗 ResNets, Regularization & Data Augmentation: https://jovian.ai/aakashns/05b-cifar1...
🔗 Simple CNN Starter Notebook: https://jovian.ai/aakashns/simple-cnn...
🔗 Transfer Learning with CNNs: https://jovian.ai/aakashns/transfer-l...
🔗 Image Classification with CNNs: https://jovian.ai/aakashns/05-cifar10...

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

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.
You can learn more and register for a Free Certificate of Accomplishment at http://zerotogans.com.

This course is taught by Aakash N S, co-founder & CEO of Jovian - a platform for sharing, showcasing and collaborating on data science projects online.

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