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