PyTorch Techniques and Ecosystem Tools

Master advanced PyTorch techniques to build high-performing, efficient deep learning models. In this course, you’ll expand your skills in hyperparameter optimization, model profiling, and workflow efficiency. You’ll experiment with learning rate schedulers, tackle overfitting, and use automated hyperparameter tuning with Optuna to boost model performance. Learn how to design flexible architectures, measure model efficiency with the PyTorch Profiler, and make the most of your compute resources.

• Optimize and hyperparameter tune PyTorch models for better performance
• Use TorchVision and Hugging Face, to efficiently process and manage image and text data, respectively
• Build efficient training pipelines for model optimization

• Intermediate PyTorch knowledge
• Deep learning concepts