Machine Learning

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Machine Learning

  • Machine learning can be useful to recommend movie at netflix
  • or how many homerun that baseball player can hit over the course of his career
Why Machine Learning useful:
  • Have some great journey along statistic
  • Grew out of computer science, many fields use it for making predictions based on data
  • predictions based on classifier, recommendation systems among the many

  • Statistic used based on existing data,drawing conclusion like for example(difference left and right batting)
  • Machine Learning focused on making predictions. It doesn't care about the data model, as long as it making right prediction (how many homerun)

  • Supervised learning learned from label data. Labeled(spam or not spam) or given parameter's of house predict (labeled house prices)

  • For example trying to separate the photos without any structure of data.

Kurt's in Twitter(social data) just focusing on the techiniques involving these data
  • Clustering (K-means, hierarchy)
  • Dimensionality reduction(PCA)
  • Often combination between the two(to understand better of cluster, using pca to reduce the dimensionality)

  • These examples is given bunch of infos predict how many homerun the players would have
  • To do this, we have some existing data (infos and homerun) to make a model
  • Feed the existing into a model and then making the prediction