Machine Learning

Description:

  • Learn and improve from “experience” without emperically programmed
  • Data-driven
    • mostly “structured”.
  • Once the training phase is over, the adaptive machines can apply their findings to real cases and make predictions, for example. If a machine learning algorithm produces inaccurate assertions, data engineers intervene and make adjustments or corrections.

Types of machine learning method:

Deep Learning

Model evaluation

Tools: