Deep Learning with PyTorch: Zero to GANs

Description

In this course, you will learn:

• Deep Learning with PyTorch: Zero to GANs" is a beginner-friendly online course delivering a practical and coding-focused introduction to deep learning using the PyTorch framework. Enroll now to start learning.

Syllabus:

1. PyTorch Basics and Gradient Descent

• PyTorch basics: tensors, gradients, and autograd
• Linear regression & gradient descent from scratch
• Using PyTorch modules: nn.Linear & nn.functional

2. All About torch.Tensor

• Explore the PyTorch documentation website
• Demonstrate usage of some tensor operations
• Publish your Jupyter notebook & share your work

3. Working with Images and Logistic Regression

• Training-validation split on the MNIST dataset
• Logistic regression, softmax & cross-entropy
• Model training, evaluation & sample predictions

4. Train Your First Model

• Download and explore a real-world dataset
• Create a linear regression model using PyTorch
• Train multiple models and make predictions

5. Training Deep Neural Networks on a GPU

• Multilayer neural networks using nn.Module
• Activation functions, non-linearity & backprop
• Training models faster using cloud GPUs

6. Feed Forward Neural Networks

• Explore the CIFAR10 image dataset
• Create a pipeline for training on GPUs
• Hyperparameter tuning & optimization

7. Image Classification with Convolutional Neural Networks

• Working with 3-channel RGB images
• Convolutions, kernels & features maps
• Training curve, underfitting & overfitting

8. Data Augmentation, Regularization & ResNets

• Adding residual layers with batchnorm to CNNs
• Learning rate annealing, weight decay & more
• Training a state-of-the-art model in 5 minutes

9. Generative Adversarial Networks and Transfer Learning

• Generating fake digits & anime faces with GANs
• Training generator and discriminator networks
• Transfer learning for image classification

10. Train a Deep Learning Model from Scratch

• Discover & explore a large real-world dataset
• Train a convolutional neural network from scratch
• Document, present, and publish your work online