Machine Learning Overview

Machine Learning Types:

• Supervised Machine Learning ~ 13-14 lectures
• Introduction to Unsupervised Learning ~ 5 lectures

Machine Learning is:

• Probably the future
• Study of algorithms that
  • improve Performance (error metric),
  • at some Task (recognizing images, etc.),
  • with Experience (from examples)
  • <P, T, E>

When do we use ML?

• Lack of expertise
• Programs that adapt through experience

ML requires:

• Access to data
• Algorithms for optimization
• Compute power

Supervised/Interactive Learning needs labels and training examples