AI - Algorithm

• Classification
  • The recommended approach
    
    • Use AUC to select the model when you do not know which threshold will be used
    • Then use FN and FP to decide the threshold
  • SVM
    • Pros
      • Accurate in high-dimensional spaces
      • Memory efficient
    • Cons
      • Prone to overfitting
      • No probability estimation
      • For small datasets
    • Applications
      • Image recognition
      • Text category assignment
      • Detecting spam
      • Sentiment  analysis
      • Gene expression classification
      • Regression, outlier detection and clustering
• CNN

  • Kernel size?

  • Recent research has shown that it's better to use smaller kernel sizes and add more convolutional layers. In other words, instead of using a nine by nine filter, try sequencing two layers of three by three filters

• RNN

• Cell_size = N_inputs // (size of the internal state in each of the cell)

• Lstm = 4 internal states

• Gru = 3

• Use custom loss function

  • E.g. use several outputs to calculate the loss

• Dropout is available
• Recommendation
  • Collaborative Filtering
    • User-based
    • Item-based
    • Challenges
      • Data sparsity
      • Cold start
      • Scalability
    • WALS: Weighted Alternating Least Squares

  • Context-aware

  • • Contextual pre-filtering, contextual post-filtering, and contextual modeling

  • Hybrid