datacamp studies

chapter 1: classification and regression trees

• decision tree for classification
  • they learn a sequence of if-else questions about features in order to infer labels
  • captures non-linear relationships between features and labels
  • decision region - region in feature space where all instances are assigned to one class label
  • decision boundary - surface separating decision regions
• classification tree learning
  • decision-tree - data structure consisting of a hierarchy of nodes (just like a normal tree)
  • a node in a decision-tree is either a question or a prediction
  • a leaf node is a prediction - all other nodes that are not leaf nodes are questions

language trilogy

started my maru hiragana drills at 18.23 and finished them in 3 minutes

18.57 - finished chapter 8 japanese busuu

19.12 - finished half of chapter 4 french busuu

19.23 - finished half of chapter 4 german busuu

was too tuckered out to do the frontend coding, maybe tomorrow