Objectives

• Work with datasets and understand tokenizer, embedding bag technique and vocabulary
• Explore embeddings in PyTorch and understand token indices
• Perform text classification using data loader and apply it on a neural network model
• Train the text classification model on a news dataset
• Engage in various exercises to solidify your understanding