What is Machine Learning

• learning:

  acquiring skill with experience accumulated from observations.

  machine learning:

  acquiring skill with experience accumulated/computed from data

• ML: an alternative route to build complicated systems.

  Some Use Scenarios:

  • when human cannot program the system manually
  • when human cannot ‘define the solution’ easily
  • when needing rapid decisions that humans cannot do
  • when needing to be user-oriented in a massive scale

  授机器以渔：）

• Key Essence of Machine Learning

  machine learning: improving some performance measure with experience computed from data.

  data->ML->improved performance measure

  1. exists some ‘underlying pattern’ to be learned
     – so ‘performance measure’ can be improved
  2. but no programmable (easy) defination
     – so ‘ML’ is needed
  3. somehow there is data about the pattern
     – so ML has some ‘inputs’ to learn from

Notes:
很多问题我们没法确定的去处理，例如判别图片中的物品、文字，但是我们希望有一种方式可以通过大量的数据输入帮我们做这样的工作，机器学习就是为了解决这些问题，授机器以渔，当然对于确定问题的处理当然传统方法分析解决更为高效。