Completed
Multi-Sensor Systems
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
Deep Probabilistic Modelling with Pyro
Automatically move to the next video in the Classroom when playback concludes
- 1 Intro
- 2 Time Series Prediction
- 3 Multi-Sensor Systems
- 4 Deep Neural Networks - Limitations
- 5 Adversarial Attacks
- 6 Neural Networks Predictions
- 7 Neural Networks Bias
- 8 Conditional Probability
- 9 Inference from Data
- 10 Probabilistic Regression
- 11 Bayes Networks
- 12 Gaussian Processes
- 13 Probabilistic Neural Networks
- 14 Probabilistic Programming Languages
- 15 Pyro - Framework
- 16 Pyro/Py Torch Example: MNIST
- 17 Neural Network Softmax Prediction
- 18 Pyro: Weight Priors
- 19 Pyro: Inference
- 20 Pyro: Variational Inference
- 21 Pyro: Loss & Training
- 22 Pyro: Sampling from the posterior
- 23 Random Noise
- 24 Predictive Maintenance Example
- 25 Sensor Data 1
- 26 Neural Network Prediction
- 27 Summary
