My PyTorch Learning Journey

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A collection of Jupyter Notebooks and resources to help me learn PyTorch and deep learning.

Table of Contents

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Notebooks

Resources

Goals

Notebooks

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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

Resources

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• PyTorch documentation
• PyTorch tutorials
• Deep learning CampusX

Goals

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• Learn the basics of PyTorch and deep learning
• Implement various deep learning architectures using PyTorch
• Apply deep learning to real-world problems

Progress

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• Complete PyTorch basics notebook
• Complete PyTorch Training Pipeline
• Implement a simple neural network using PyTorch
• Model Training using Dataset and Dataloader Class