Data analysis and machine learning

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Matlab is mostly, at its heart, a data analysis tool. Whether you are loading and visualizing datasets along interesting dimensions, or extracting underlying components using more advanced tools akin to machine learning, you are essentially doing some data analysis. No ressources about Matlab would be complete without an extensive description of how to use it to perform data analysis. In this section of Matlabtips.com, I hope to slowly but surely build a  collection of ressources on how to perform data analysis in Matlab. This particular topic is so large that there is enough to cover for many years, so please come often for some new posts!

  1. Supervised vs Unsupervised learning (to be done).
  2. Supervised learning
    1. Data fitting (to be done)
    2. Overfitting (to be done)
    3. Neural network  (to be done)
    4. Support Vector Machine (to be done)
  3. Unsupervised learning
    1. Principal Component Analysis (PCA) demystified
    2. Independent Component Analysis (ICA) demystified
    3. K-Means clustering