LFD473: PyTorch in Practice - An Applications-First Approach Part I: Training a Model in PyTorch PyTorch, Datasets. and Models Building Your First Dataset Lab 1A: Non-Linear Regression / Solution Training Your First Model Lab 1B: Non-Linear Regression / Solution Building Your First Datapipe Lab 2: Price Prediction / Solution Part II: Transfer Learning Transfer Learning and Pretrained Models Lab 3: Classifying Images / Solutions Pretrained Models for Computer Vision Pretrained Models for Natural Language Processing Lab 4: Sentiment Analysis / Solutions Part III: Computer Vision Image Classification with Torchvision Fine-Tuning Pretrained Models for Computer Vision Serving Models with TorchServe Datasets and Transformations for Object Detection and Image Segmentation Lab 5A: Fine-Tuning Object Detection Models / Solutions Models for Object Detection and Image Segmentation Lab 5B: Fine-Tuning Object Detection Models / Solutions Models for Object Detection Evaluation Part IV: Natural Language Processing Word Embeddings and Text Classification Lab 6: Text Classification / Solutions Contextual Word Embeddings with Transformers HuggingFace Pipelines for NLP Tasks Lab 7: Document Q&A / Solutions Question and Answer, Summarization, and LLMs