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All LessonsFree Lessons (4)

Introduction

Overview of Image Classification Image Classification Techniques Image Classification Metrics PyTorch Image Model Framework

Basic Concepts

Create Model List and Search Supported Models Dataset Format Load and Preprocess Images Prediction Using Pre-trained Resnet50 Prediction Using Pre-trained EfficientNet Quiz (Basic)Exercise (Basic)

Augmentation

Training a Neural Network with Augmentation

Mixup and Cutmix

Random Resized Crop and Interpolation

Quiz (Augmentation)

Loss

Loss Functions Asymmetric Loss Jensen-Shannon Divergence and Cross-Entropy Loss Quiz (Loss)

Training

Training Workflow ResNet50 EfficientNet Fine-tuning Custom Model Training with an EMA (Exponential Moving Average)Quiz (Training)Exercise (Training)

Model Conversion

Serving a Pytorch Model Convert PyTorch Model into an ONNX Model Serving an ONNX Model Convert ONNX into a Tensorflow Model Serving a TensorFlow Model Convert a TensorFlow Model into a TFLite Model Serving a TFLite Model Quiz (Model Conversion)Exercise (Model Conversion)

Project

Anomaly Detection in Medical Images: Python, TF, and PyTorch

Deployment

Overview of FastAPI HTTP Methods REST API Integration Quiz (Deployment)Exercise (Deployment)

Appendix

Virtual Environment Python Packages Package Installation Training Arguments Deployment Dependencies

Conclusion

Getting Started with Image Classification with PyTorch/

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Quiz (Augmentation)

Quiz (Augmentation)

Test your knowledge of the data augmentations in the PyTorch Image Model.

We'll cover the following...

Augmentation

1.

What is the default image augmentation in the PyTorch Image Model framework?

A.

RandAugment

B.

AutoAugment

C.

Random Erase

D.

Random resized crop and interpolation

E.

Mixup and Cutmix

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