Description
Is there an existing issue for this?
- I have searched the existing issues
Feature Description
Bayesian Optimization is a sequential model-based optimization technique that uses Bayesian inference to direct the search for the optimal set of hyperparameters in machine learning models. Unlike grid search or random search, Bayesian Optimization builds a probabilistic model of the objective function and uses it to select the most promising hyperparameters to evaluate, thereby optimizing performance with fewer evaluations.
Use Case
In a real-time use case, a data scientist working on a time-sensitive project like crude oil price forecasting can use Bayesian Optimization to quickly identify the best hyperparameters for their predictive model. This leads to more accurate predictions with reduced computational resources, enabling timely and informed decision-making in the energy sector.
Benefits
No response
Add ScreenShots
No response
Priority
High
Record
- I have read the Contributing Guidelines
- I'm a GSSOC'24 contributor
- I have starred the repository