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A collection of Jupyter Notebooks and resources to help me learn PyTorch and deep learning.
This repository contains a series of Jupyter Notebooks that cover various topics in PyTorch and deep learning, including:
- PyTorch basics
- Neural networks
- Convolutional neural networks (CNNs)
- Recurrent neural networks (RNNs)
- Transfer learning
- Long-Short term memory(LSTMs)
- seq2seq model
- seq2seq model with attention
- Transformer
- Fine-tuning LM
- PyTorch documentation
- PyTorch tutorials
- Deep learning CampusX
- Learn the basics of PyTorch and deep learning
- Implement various deep learning architectures using PyTorch
- Apply deep learning to real-world problems
- Complete PyTorch basics notebook
- Complete PyTorch Training Pipeline
- Implement a simple neural network using PyTorch
- Model Training using Dataset and Dataloader Class