Update links to examples.

docs/source/faq.rst

@@ -8,7 +8,7 @@ Can I use Optuna with X? (where X is your favorite ML library)
 --------------------------------------------------------------
 
 Optuna is compatible with most ML libraries, and it's easy to use Optuna with those.
-Please refer to `examples <https://github.com/optuna/optuna/tree/master/examples>`_.
+Please refer to `examples <https://github.com/optuna/optuna-examples/>`_.
 
 
 .. _objective-func-additional-args:
@@ -63,7 +63,7 @@ Below is an example that uses ``lambda``:
     study = optuna.create_study()
     study.optimize(lambda trial: objective(trial, min_x, max_x), n_trials=100)
 
-Please also refer to `sklearn_addtitional_args.py <https://github.com/optuna/optuna/blob/master/examples/sklearn/sklearn_additional_args.py>`_ example,
+Please also refer to `sklearn_addtitional_args.py <https://github.com/optuna/optuna-examples/tree/main/sklearn/sklearn_additional_args.py>`_ example,
 which reuses the dataset instead of loading it in each trial execution.
 
 

tutorial/10_key_features/002_configurations.py

@@ -49,7 +49,7 @@ def objective(trial):
 #
 # Also, you can use branches or loops depending on the parameter values.
 #
-# For more various use, see `examples <https://github.com/optuna/optuna/tree/master/examples>`_.
+# For more various use, see `examples <https://github.com/optuna/optuna-examples/>`_.
 
 ###################################################################################################
 # - Branches:

tutorial/10_key_features/003_efficient_optimization_algorithms.py

@@ -80,7 +80,7 @@
 # :func:`~optuna.trial.Trial.should_prune` decides termination of the trial that does not meet a predefined condition.
 #
 # We would recommend using integration modules for major machine learning frameworks.
-# Exclusive list is :mod:`optuna.integration` and usecases are available in  `optuna/examples <https://github.com/optuna/optuna/tree/master/examples/>`_.
+# Exclusive list is :mod:`optuna.integration` and usecases are available in  `optuna/examples <https://github.com/optuna/optuna-examples/>`_.
 
 
 import logging
@@ -163,7 +163,7 @@ def objective(trial):
 # For the complete list of Optuna's integration modules, see :mod:`optuna.integration`.
 #
 # For example, :class:`~optuna.integration.XGBoostPruningCallback` introduces pruning without directly changing the logic of training iteration.
-# (See also `example <https://github.com/optuna/optuna/blob/master/examples/xgboost/xgboost_integration.py>`_ for the entire script.)
+# (See also `example <https://github.com/optuna/optuna-examples/tree/main/xgboost/xgboost_integration.py>`_ for the entire script.)
 #
 # .. code-block:: python
 #