This is a repository which looks at Deep learning tutorial with Pytorch, with various important functions and documentation.
The repository holds the code and the explanation of code to help beginners and advance you upto an advanced developer.
- Introduction to PyTorch Tensors: Create Tensors, Conversion to and from Numpy, Addition and Multiplication between tensors.
- Neural Networks with PyTorch: Define a fully connected neural network, Understand multiple ways to define a network.
- Training Neural Networks: Train MNIST dataset with fully connected network - Loss, Backpropagation and Epochs.
- Fashion MNIST: Training Fashion MNIST dataset with fully connected network.
- Inference and Validation: Training and Evaluation Mode - Fashion MNIST.
- Saving and Loading Model: Model persistence.
- Loading image data: Introduction to TorchVision and Data Augmentation.
- Fully connected on MNIST: Create fully connected network, with data loaders.
- Validation set from MNIST: Understanding and Implementing validation sets.
Install all the depenecies using pip install -r requirements.txt