Lesson 5 - Data Augmentation, Regularization & ResNets
Deep Learning with PyTorch: Zero to GANs
Course HomeLesson 1 - PyTorch Basics and Gradient DescentAssignment 1 - All About torch.TensorLesson 2 - Working with Images and Logistic RegressionAssignment 2 - Train Your First ModelLesson 3 - Training Deep Neural Networks on a GPUAssignment 3 - Feed Forward Neural NetworksLesson 4 - Image Classification with Convolutional Neural Networks
Next →
Hindi Version: https://youtu.be/S2zNff6rgOg
This lesson covers some advanced techniques like data augmentation, regularization, and adding residual layers to convolutional neural networks. We train a state-of-the-art model from scratch in just five minutes. Notebooks used in this lesson:
- ResNets, Regularization & Data Augmentation: https://jovian.ai/aakashns/05b-cifar10-resnet
- Simple CNN Starter Notebook: https://jovian.ai/aakashns/simple-cnn-starter
- Transfer Learning with CNNs: https://jovian.ai/aakashns/transfer-learning-pytorch
- Image Classification with CNNs: https://jovian.ai/aakashns/05-cifar10-cnn
Ask questions and get help on the course discussion forum
aakashns/05b-cifar10-resnet
aakashns/05-cifar10-cnn
aakashns/transfer-learning-human-protein
Loading...