lectures.alex.balgavy.eu

Lecture notes from university.
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      1 +++
      2 title = 'Machine Learning for the Quantified Self'
      3 +++
      4 
      5 # Machine Learning for the Quantified Self
      6 1. [Introduction & Basics of Sensory Data](introduction-basics-of-sensory-data)
      7 2. [Handling sensory noise](handling-sensory-noise)
      8 3. [Feature engineering](feature-engineering)
      9 4. [Clustering](clustering)
     10 5. [Supervised learning](supervised-learning)
     11 
     12 [A good video on dynamic time warping](https://www.youtube.com/watch?v=_K1OsqCicBY).
     13 You can test it out yourself with [the dtw package](https://dynamictimewarping.github.io/) in R and Python.
     14 
     15 I used Anki to study for the exam, [here's the Anki deck](ML4QS.apkg).