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Add HPO execution options and additional notes (#364)

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title: Hyperparameter Optimization
---
## What is HyperParameter Optimization?
## What is Hyperparameter Optimization?
Hyperparameters are variables that directly control the behaviors of training algorithms, and have a significant effect on
the performance of the resulting machine learning models. Finding the hyperparameter values that yield the best
performing models can be complicated. Manually adjusting hyperparameters over the course of many training trials can be
slow and tedious. Luckily, you can automate and boost hyperparameter optimization with ClearML's
[**`HyperParameterOptimizer`**](../references/sdk/hpo_optimization_hyperparameteroptimizer.md) class.
## ClearML's HyperParameter Optimization
## ClearML's Hyperparameter Optimization
ClearML provides the `HyperParameterOptimizer` class, which takes care of the entire optimization process for users
with a simple interface.
@ -115,17 +115,35 @@ optimization.
max_iteration_per_job=150000,
)
```
<br/>
:::tip Locating Task ID
To locate the base task's ID, go to the task's info panel in the [WebApp](../webapp/webapp_overview.md). The ID appears
in the task header.
:::
:::tip Locating Task ID
To locate the base task's ID, go to the task's info panel in the [WebApp](../webapp/webapp_overview.md). The ID appears
in the task header.
:::
For more information about `HyperParameterOptimizer` and supported optimization modules, see the [HyperParameterOptimizer class reference](../references/sdk/hpo_optimization_hyperparameteroptimizer.md).
## Optimizer Execution Options
The `HyperParameterOptimizer` provides options to launch the optimization tasks locally or through a ClearML [queue](agents_and_queues.md#what-is-a-queue).
Start a `HyperParameterOptimizer` instance using either [`HyperParameterOptimizer.start`](../references/sdk/hpo_optimization_hyperparameteroptimizer.md#start)
or [`HyperParameterOptimizer.start_locally`](../references/sdk/hpo_optimization_hyperparameteroptimizer.md#start_locally).
Both methods run the optimizer controller locally. The `start` method launches the base task clones through a queue
specified when instantiating the controller, while `start_locally` runs the tasks locally.
:::tip Remote Execution
You can also launch the optimizer controller through a queue by using the [`Task.execute_remotely`](../references/sdk/task.md#execute_remotely)
method before starting the optimizer.
:::
## Tutorial
Check out the [Hyperparameter Optimization tutorial](../guides/optimization/hyper-parameter-optimization/examples_hyperparam_opt.md) for a step-by-step guide.
## Hyperparameter Optimization CLI
ClearML also provides `clearml-param-search`, a CLI utility for managing the hyperparameter optimization process. See
[ClearML Param Search](../apps/clearml_param_search.md) for more information.
## SDK Reference
For detailed information, see the complete [HyperParameterOptimizer SDK reference page](../references/sdk/hpo_optimization_hyperparameteroptimizer.md).