Update links (#1041)

docs/getting_started/ds/ds_second_steps.md

@@ -89,7 +89,7 @@ Calling `get_local_copy()` returns a local cached copy of the artifact. Therefor
 need to download the artifact again.
 Calling `get()` gets a deserialized pickled object.
 
-Check out the [artifacts retrieval](https://github.com/allegroai/clearml/blob/master/examples/reporting/artifacts_retrieval.py) example code.
+Check out the [artifacts retrieval](https://github.com/clearml/clearml/blob/master/examples/reporting/artifacts_retrieval.py) example code.
 
 ### Models
 
@@ -112,10 +112,10 @@ Now, whenever the framework (TensorFlow/Keras/PyTorch etc.) stores a snapshot, t
 Loading models by a framework is also logged by the system; these models appear in an experiment's **Artifacts** tab,
 under the "Input Models" section.
 
-Check out model snapshots examples for [TensorFlow](https://github.com/allegroai/clearml/blob/master/examples/frameworks/tensorflow/tensorflow_mnist.py),
-[PyTorch](https://github.com/allegroai/clearml/blob/master/examples/frameworks/pytorch/pytorch_mnist.py),
-[Keras](https://github.com/allegroai/clearml/blob/master/examples/frameworks/keras/keras_tensorboard.py),
-[scikit-learn](https://github.com/allegroai/clearml/blob/master/examples/frameworks/scikit-learn/sklearn_joblib_example.py).
+Check out model snapshots examples for [TensorFlow](https://github.com/clearml/clearml/blob/master/examples/frameworks/tensorflow/tensorflow_mnist.py),
+[PyTorch](https://github.com/clearml/clearml/blob/master/examples/frameworks/pytorch/pytorch_mnist.py),
+[Keras](https://github.com/clearml/clearml/blob/master/examples/frameworks/keras/keras_tensorboard.py),
+[scikit-learn](https://github.com/clearml/clearml/blob/master/examples/frameworks/scikit-learn/sklearn_joblib_example.py).
 
 #### Loading Models
 Loading a previously trained model is quite similar to loading artifacts.

docs/getting_started/main.md

@@ -35,19 +35,19 @@ training, and deploying models at every scale on any AI infrastructure.
 <table>
 <tbody>
   <tr>
-    <td><a href="https://github.com/allegroai/clearml/blob/master/docs/tutorials/Getting_Started_1_Experiment_Management.ipynb"><b>Step 1</b></a> - Experiment Management</td>
+    <td><a href="https://github.com/clearml/clearml/blob/master/docs/tutorials/Getting_Started_1_Experiment_Management.ipynb"><b>Step 1</b></a> - Experiment Management</td>
     <td className="align-center"><a className="no-ext-icon" target="_blank" href="https://colab.research.google.com/github/allegroai/clearml/blob/master/docs/tutorials/Getting_Started_1_Experiment_Management.ipynb">
   <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
 </a></td>
   </tr>
   <tr>
-    <td><a href="https://github.com/allegroai/clearml/blob/master/docs/tutorials/Getting_Started_2_Setting_Up_Agent.ipynb"><b>Step 2</b></a> - Remote Execution Agent Setup</td>
+    <td><a href="https://github.com/clearml/clearml/blob/master/docs/tutorials/Getting_Started_2_Setting_Up_Agent.ipynb"><b>Step 2</b></a> - Remote Execution Agent Setup</td>
     <td className="align-center"><a className="no-ext-icon" target="_blank" href="https://colab.research.google.com/github/allegroai/clearml/blob/master/docs/tutorials/Getting_Started_2_Setting_Up_Agent.ipynb">
   <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
 </a></td>
   </tr>
   <tr>
-    <td><a href="https://github.com/allegroai/clearml/blob/master/docs/tutorials/Getting_Started_3_Remote_Execution.ipynb"><b>Step 3</b></a> - Remotely Execute Tasks</td>
+    <td><a href="https://github.com/clearml/clearml/blob/master/docs/tutorials/Getting_Started_3_Remote_Execution.ipynb"><b>Step 3</b></a> - Remotely Execute Tasks</td>
     <td className="align-center"><a className="no-ext-icon" target="_blank" href="https://colab.research.google.com/github/allegroai/clearml/blob/master/docs/tutorials/Getting_Started_3_Remote_Execution.ipynb">
   <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
 </a></td>

docs/getting_started/mlops/mlops_first_steps.md

@@ -39,7 +39,7 @@ required Python packages, and execute and monitor the process.
     ```
 
     :::note
-    If you've already created credentials, you can copy-paste the default agent section from [here](https://github.com/allegroai/clearml-agent/blob/master/docs/clearml.conf#L15) (this is optional. If the section is not provided the default values will be used)
+    If you've already created credentials, you can copy-paste the default agent section from [here](https://github.com/clearml/clearml-agent/blob/master/docs/clearml.conf#L15) (this is optional. If the section is not provided the default values will be used)
     :::
 
 1. Start the agent's daemon and assign it to a [queue](../../fundamentals/agents_and_queues.md#what-is-a-queue):

docs/getting_started/video_tutorials/quick_introduction.md

@@ -32,6 +32,6 @@ It's essentially a toolbox stuffed with everything you'll need to go from experi
 
 Doesn't matter if you're starting small or already in production, there's always a ClearML tool that can make your life easier.
 
-Start for free at [app.clear.ml](https://app.clear.ml) or host your own server from our [GitHub page](https://github.com/allegroai/clearml-server).
+Start for free at [app.clear.ml](https://app.clear.ml) or host your own server from our [GitHub page](https://github.com/clearml/clearml-server).
 
 </Collapsible>