# Table of Contents for Notebooks Here you can find a list of notebooks that contain accompanying and hands-on material to the chapters you find in this course. Feel free to browse them at your own speed and interest. | Chapter Title | Notebooks | Colabs | | ------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Unit 0 - Welcome | No Notebook | No Colab | | Unit 1 - Fundamentals | No Notebook | No Colab | | Unit 2 - Convolutional Neural Networks | [Transfer Learning with VGG19](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%202%20-%20Convolutional%20Neural%20Networks/transfer_learning_vgg19.ipynb) | [Transfer Learning with VGG](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%202%20-%20Convolutional%20Neural%20Networks/transfer_learning_vgg19.ipynb) | | | [Using ResNet with timm](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%202%20-%20Convolutional%20Neural%20Networks/timm_Resnet.ipynb) | [timm_Resnet](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%202%20-%20Convolutional%20Neural%20Networks/timm_Resnet.ipynb) | | Unit 3 - Vision Transformers | [Detection Transformer (DETR)](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/DETR.ipynb) | [Detection Transformer (DETR)](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/DETR.ipynb) | | | [Fine-tuning Vision Transformers for Object Detection](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/Fine-tuning%20Vision%20Transformers%20for%20Object%20detection.ipynb) | [Fine-tuning Vision Transformers for Object Detection](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/Fine-tuning%20Vision%20Transformers%20for%20Object%20detection.ipynb) | | | [Knowledge Distillation](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/KnowledgeDistillation.ipynb) | [Knowledge Distillation](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/KnowledgeDistillation.ipynb) | | | [LoRA Fine-tuning for Image Classification](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/LoRA-Image-Classification.ipynb) | [LoRA Fine-tuning for Image Classification](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/LoRA-Image-Classification.ipynb) | | | [Fine-tuning for Multilabel Image Classification](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/fine-tuning-multilabel-image-classification.ipynb) | [Fine-tuning for Multilabel Image Classification](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/fine-tuning-multilabel-image-classification.ipynb) | | | [Transfer Learning for Image Classification](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/transfer-learning-image-classification.ipynb) | [Transfer Learning for Image Classification](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/transfer-learning-image-classification.ipynb) | | | [Transfer Learning for Image Segmentation](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/transfer-learning-segmentation.ipynb) | [Transfer Learning for Image Segmentation](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/transfer-learning-segmentation.ipynb) | | | [Swin Transformer](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/Swin.ipynb) | [Swin Transformer](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/Swin.ipynb) | | Unit 4 - Multimodal Models | [Clip Crop](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/ClipCrop.ipynb) | [Clip Crop](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/ClipCrop.ipynb) | | | [Fine-tuning CLIP](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/Clip_finetune.ipynb) | [Fine-tuning CLIP](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/Clip_finetune.ipynb) | | | [Clustering with CLIP](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Clustering%20with%20CLIP.ipynb) | [Clustering with CLIP](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Clustering%20with%20CLIP.ipynb) | | | [Image Classification with CLIP](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Image%20classification%20with%20CLIP.ipynb) | [Image Classification with CLIP](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Image%20classification%20with%20CLIP.ipynb) | | | [Image Retrieval with Prompts](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Image_retrieval_with_prompts.ipynb) | [Image Retrieval with Prompts](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Image_retrieval_with_prompts.ipynb) | | | [Image Similarity](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Image_similarity.ipynb) | [Image Similarity](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Image_similarity.ipynb) | | Unit 5 - Generative Models | No Notebook | No Colab | | Unit 6 - Basic CV Tasks | [Fine-tune SAM on Custom Dataset]() | [Fine-tune SAM on Custom Dataset]() | | Unit 7 - Video and Video Processing | [Fine-tune ViViT for Video Classification](https://github.com/DiwakarBasnet/computer-vision-course/blob/unit-7_Video_and_VideoProcessing/notebooks/Unit%207%20-%20Video%20and%20Video%20Processing/Vivit_Fine_tuned_Video_Classification.ipynb) | [Fine-tune ViViT for Video Classification](https://github.com/DiwakarBasnet/computervisioncourse/blob/unit7_Video_and_VideoProcessing/notebooks/Unit%207%20%20Video%20and%20Video%20Processing/Vivit_Fine_tuned_Video_Classification.ipynb) | | Unit 8 - 3D Vision, Scene Rendering, and Reconstruction | No Notebook | No Colab | | Unit 9 - Model Optimization | [Edge TPU](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/edge_tpu.ipynb) | [Edge TPU](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/edge_tpu.ipynb) | | | [ONNX](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/onnx.ipynb) | [ONNX](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/onnx.ipynb) | | | [OpenVINO](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/openvino.ipynb) | [OpenVINO](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/openvino.ipynb) | | | [Optimum](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/optimum.ipynb) | [Optimum](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/optimum.ipynb) | | | [TensorRT](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/tensorrt.ipynb) | [TensorRT](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/tensorrt.ipynb) | | | [TMO](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/tmo.ipynb) | [TMO](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/tmo.ipynb) | | | [Torch](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/torch.ipynb) | [Torch](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/torch.ipynb) | | Unit 10 - Synthetic Data Creation | [Dataset Labeling with OWLv2](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/OWLV2_labeled_image_dataset_with_annotations.ipynb) | [Dataset Labeling with OWLv2](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/OWLV2_labeled_image_dataset_with_annotations.ipynb) | | | [Generating Synthetic Lung Images](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/Synthetic_lung_images_hf_course.ipynb) | [Generating Synthetic Lung Images](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/Synthetic_lung_images_hf_course.ipynb) | | | [BlenderProc Examples](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/blenderproc_examples.ipynb) | [BlenderProc Examples](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/blenderproc_examples.ipynb) | | | [Image Labeling with BLIP-2](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/image_labeling_BLIP_2.ipynb) | [Image Labeling with BLIP-2](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/image_labeling_BLIP_2.ipynb) | | | [Synthetic Data Creation with SDXL Turbo](https://github.com/huggingface/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/synthetic_data_creation_sdxl_turbo.ipynb) | [Synthetic Data Creation with SDXL Turbo](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/synthetic_data_creation_sdxl_turbo.ipynb) | | Unit 11 - Zero Shot Computer Vision | No Notebook | No Colab | | Unit 12 - Ethics and Biases | No Notebook | No Colab | | Unit 13 - Outlook | No Notebook | No Colab |