Neural Networks Notes

Lectures

1A

Machine learning is good for complicated processes combining weak rules to hit a moving target. The machine learning approach is to mine data for rules and it should work for new cases, not just the cases it was trained on.

Best for learning algorithms:

• Recognizing patterns
  • objects in real scenes
  • facial identities or expressions
  • spoken words
• Anomalies
  • unusual sequences of credit card transactions
  • unusual patterns of sensor readings in nuclear power plants
• Prediction
  • future stock prices
  • which movies a person will like

The MNIST database of hand-written digits is the machine learning equivalent of fruit flies to genetics. TIMIT is the same benchmark for speech recognition.