1. Optimizing a Machine Learning /Artificial Intelligence Solution
  2. ML Problem Formulation: Setting the Right Objective
  3. Data Collection and Pre-processing
  4. Model Evaluation and Debugging
  5. Imbalanced Machine Learning
  6. Hyper-parameter Tuning
  7. Parameter Optimization Algorithms
  8. Optimizing Deep Learning Models
  9. Optimizing Image Models
  10. Optimizing Natural Language Processing Models
  11. Transfer Learning