I’m presenting here a summary I’ve written of the key concepts, illustrations, otpimisaton program and limitations for the most common types of algorithms. Don’t hesitate to drop a comment !

We’ll cover :

  • Bayes classifier
  • Linear Discriminant Analysis (LDA)
  • Quadratic Discriminant Analysis (QDA)
  • Naive Bayes Classifier
  • Perceptron
  • Logistic Regression
  • K-Nearest Neighbors (KNN)
  • Local Averaging
  • Decision Tree
  • Support Vector Machine (SVM)
  • Bagging
  • Random Forest
  • Extra Trees
  • Boosting
  • Gradient Boosting
  • Depth Based Models
  • Depth KNN

Click on the image below to load the PDF summary :


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