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How much is this car worth?
Machine Learning Problem Example
Mileage
Condition
Car brand
Year of make
Regulations
…
Parameter 1
Parameter 2
Parameter 3
Parameter 4
…
Gradient Boosted
Nearest Neighbors
SVM
Bayesian Regression
LGBM
…
Mileage Gradient Boosted Criterion
Loss
Min Samples Split
Min Samples Leaf
Others Model
Which algorithm? Which parameters?Which features?
Car brand
Year of make
Criterion
Loss
Min Samples Split
Min Samples Leaf
Others
N Neighbors
Weights
Metric
P
Others
Which algorithm? Which parameters?Which features?
Mileage
Condition
Car brand
Year of make
Regulations
…
Gradient Boosted
Nearest Neighbors
SVM
Bayesian Regression
LGBM
…
Nearest Neighbors
Model
Iterate
Gradient BoostedMileage
Car brand
Year of make
Car brand
Year of make
Condition
Which algorithm? Which parameters?Which features?
Iterate
Enter data
Define goals
Apply constraints
OutputInput Intelligently test multiple models in parallel
Optimized model
AI for AI: Building state of the art models
AI for AI: Building state of the art models
AI for AI: Building state of the art models
AI for AI: Building state of the art models
AI for AI: Building state of the art models

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AI for AI: Building state of the art models

  • 1.
  • 2.
  • 3.
  • 4. How much is this car worth? Machine Learning Problem Example
  • 5. Mileage Condition Car brand Year of make Regulations … Parameter 1 Parameter 2 Parameter 3 Parameter 4 … Gradient Boosted Nearest Neighbors SVM Bayesian Regression LGBM … Mileage Gradient Boosted Criterion Loss Min Samples Split Min Samples Leaf Others Model Which algorithm? Which parameters?Which features? Car brand Year of make
  • 6. Criterion Loss Min Samples Split Min Samples Leaf Others N Neighbors Weights Metric P Others Which algorithm? Which parameters?Which features? Mileage Condition Car brand Year of make Regulations … Gradient Boosted Nearest Neighbors SVM Bayesian Regression LGBM … Nearest Neighbors Model Iterate Gradient BoostedMileage Car brand Year of make Car brand Year of make Condition
  • 7. Which algorithm? Which parameters?Which features? Iterate
  • 8. Enter data Define goals Apply constraints OutputInput Intelligently test multiple models in parallel Optimized model