Chapters (7)
- 0:00Introduction
- 3:25PyTorch Basics & Linear Regression
- 1:32:15Image Classification with Logistic Regression
- 3:06:59Training Deep Neural Networks on a GPU with PyTorch
- 4:44:51Image Classification using Convolutional Neural Networks
- 6:35:11Residual Networks, Data Augmentation and Regularization
- 8:12:08Training Generative Adverserial Networks (GANs)
Show the creator's full description
In this course, you will learn how to build deep learning models with PyTorch and Python. The course makes PyTorch a bit more approachable for people starting out with deep learning and neural networks.
💻 Code:
https://jovian.ml/aakashns/01-pytorch-basics
https://jovian.ml/aakashns/02-linear-regression
https://jovian.ml/aakashns/03-logistic-regression
https://jovian.ml/aakashns/04-feedforward-nn
https://jovian.ml/aakashns/05-cifar10-cnn
https://jovian.ml/aakashns/05b-cifar10-resnet
https://jovian.ml/aakashns/06-mnist-gan
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⭐️ Course Contents ⭐️
⌨️ (0:00:00) Introduction
⌨️ (0:03:25) PyTorch Basics & Linear Regression
⌨️ (1:32:15) Image Classification with Logistic Regression
⌨️ (3:06:59) Training Deep Neural Networks on a GPU with PyTorch
⌨️ (4:44:51) Image Classification using Convolutional Neural Networks
⌨️ (6:35:11) Residual Networks, Data Augmentation and Regularization
⌨️ (8:12:08) Training Generative Adverserial Networks (GANs)
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