Machine learning notes

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  1. 1. What is machine learning?
  2. 2. Steps of Sovling a Problem

  • What is machine learning?

  • Core Task
    • Finds patterns in data
    • Use those patterns to predict future

Example Machine Learning Offerings

  • What is learning?
    • Identifying patterns
    • Recognizing those patterns when you see them again

Machine can find a pattern in existing data, then create and use a model that recognize those patterns in new data

Inside Machine Learning

  • A Data Scientist needs to master

    • statistics
    • machine learning software
    • some problem domain (application fields)

  • Languages

    • R
    • Python

  • Steps of Sovling a Problem

  • Ask a question first? such as…
    • How to keep a player to play longer?
    • How to get a player to play instantly?

1st Step of Machine Learning

  • Whether or not having lots of right data?

  • Pattern, Model and Application?

Machine Learning Process

  • Need knowledge:
    • Training data: the prepared data used to create a model
    • Supervised learning: the value you want to predict is in the training data, data is labelled, the target value is part of training data.
      (and unsupervised learning)
    • Classifying machine learning problems and algorithms
      • Supervised: Regression, Classification,
      • Unsupervised: Clustering Algorithms: Decision tree, Neural network, Bayesian, K-means

Repeating Machine Learning Process

  1. Training a model
  2. Testing a model
  3. Using a model