Tutorials

• 1. Structuring the input
  • Time-series dataset implementations
  • Loading batches of data using DataLoader
  • Handling data splits (train, validation, and test) using LightningDataModule
  • Summary
• 2. Training a Pytorch Lighning model
  • Creating KuHar LightningDataModule
  • Training a simple model
  • Testing the model
• 3. Training a self-supervised model: Contrastive Predictive Coding (CPC)
  • Pre-training the model
  • Fine-tuning the model
  • Next steps
• 4. Using Experiments
  • Experiment Structure
  • Running CPC Experiment
  • Experiment: Evaluating CPC Performance
  • Other advantages of using LightningExperiment
• 5. Training an Anomaly Detection Model for Covid Anomaly Detection
  • Overview
  • Training
  • Predicting