How do you choose which ML model to use?

Question

Accepted Answer

The choice of ML model depends on the problem, data, and desired outcome.

Consider the problem type: classification, regression, clustering, etc.
Analyze the data: size, quality, features, and target variable.
Evaluate model performance: accuracy, precision, recall, F1-score.
Consider interpretability, scalability, and computational requirements.
Experiment with multiple models: decision trees, SVM, neural networks, etc.
Use cross-validation and hyperparameter tuning for model selection.
Consider ensemble methods for improved performance.
Example: Use logistic regression for binary classification with interpretable results.
Example: Use random forest for high-dimensional data with complex relationships.

Accepted Answer

it totaly depend on your data,basicaly model selection is hypertune parameter

Accenture Data Scientist interview questions & answers