Machine(s) Learning with Neural Networks
A basic introduction to Machine Learning and Neural Networks using Python.
Slides can be found here: www.slideshare.net/bgoncalves/machines-learning-with-neural-networks
Topics
- References
- How the brain works (Cartoon version)
- Supervised Learning - Classification
- Supervised Learning - Overfitting
- Bias-Variance Tradeoff
- Perceptron
- Activation Function
- Perceptron - Forward Propagation
- Perceptron - Training
- Forward Propagation
- Backward Propagation of Errors (BackProp)
- Chain Rule
- Loss Functions
- A Practical Example - MNIST
- MNIST - BackProp
- MNIST - Training
- Bias-Variance Tradeoff
- Learning Rate
- Tips
- Neural Network Architectures
- Interpretability
- "Deep" Learning
