Artificial Intelligence

Course Content

Total learning: 10 lessons

Part – 5

Various Outcomes-Based MLP And Regularization Techniques

  • Binary classification problem using MLP on IMDB dataset
  • Multi-class classification problem using MLP on Reuters dataset
  • Regression problem using MLP on Boston Housing dataset
  • Types of Machine Learning outcomes – Self-supervised, Reinforcement Learning, etc.
  • Handling imbalanced datasets and avoiding overfitting and underfitting
  • Simple hold-out validation
  • K-Fold validation
  • Iterated K-fold validation with shuffling
  • Adding weight regularization
  • L1 regularization
  • L2 regularization
  • Drop Out and Drop Connect
  • Early Stopping
  • Adding Noise – Data Noise, Label Noise, Gradient Noise
  • Batch Normalization
  • Data Augmentation
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