[YOLOv7 tutorials] - fix typo

Author: eleapttn

pages/platform/ai/deploy_tuto_13_streamlit_yolov7/guide.en-gb.md

@@ -11,7 +11,7 @@ updated: 2023-03-31
 
 ## Objective
 
-The purpose of this tutorial is to show how to deploy a web service to recognize **Amercian Sign Language letters** using YOLOv7 model.
+The purpose of this tutorial is to show how to deploy a web service to recognize **American Sign Language letters** using YOLOv7 model.
 
 In order to do this, you will use [Streamlit](https://streamlit.io/), a Python framework that turns scripts into a shareable web application. You will also learn how to build and use a custom Docker image for a Streamlit application.
 
@@ -60,7 +60,7 @@ import io
 import os
 ```
 
-Load the **YOLOv7** model and your own weights. Put this function it in **cache**:
+Load the **YOLOv7** model and your own weights. Put this function in **cache**:
 
 ```python
 @st.cache
@@ -175,7 +175,7 @@ pyyaml==6.0
 
 ### Write the Dockerfile for the application
 
-Your Dockerfile should start with the the `FROM` instruction indicating the parent image to use. In our case we choose to start from a `python:3.8` image:
+Your Dockerfile should start with the `FROM` instruction indicating the parent image to use. In our case we choose to start from a `python:3.8` image:
 
 ```console
 FROM python:3.8
@@ -200,7 +200,7 @@ Define your default launching command to start the application:
 CMD [ "streamlit" , "run" , "/workspace/main.py", "--server.address=0.0.0.0" ]
 ```
 
-Give correct access rights to **ovhcloud user** (`42420:42420`):
+Give correct access rights to **OVHcloud user** (`42420:42420`):
 
 ```console
 RUN chown -R 42420:42420 /workspace
@@ -242,13 +242,13 @@ Once started, your application should be available on `http://localhost:8501`.
 > **Warning**
 > The shared registry of AI Deploy should only be used for testing purpose. Please consider attaching your own Docker registry. More information about this can be found [here](https://docs.ovh.com/gb/en/publiccloud/ai/training/add-private-registry).
 
-Find the adress of your shared registry by launching this command:
+Find the address of your shared registry by launching this command:
 
 ```console
 ovhai registry list
 ```
 
-Login on the shared registry with your usual openstack credentials:
+Log in to the shared registry with your usual OpenStack credentials:
 
 ```console
 docker login -u <user> -p <password> <shared-registry-address>

pages/platform/ai/notebook_tuto_11_yolov7/guide.en-gb.md

@@ -11,7 +11,7 @@ updated: 2023-03-10
 
 ## Objective
 
-The purpose of this tutorial is to show how it is possible to train YOLOv7 to recognize **American Sign Language letters**. YOLOv7 is an object detection algorithm. Although closely related to image classification, object detection performs image classification on a more precise scale. Object detection locates and categories features in images.
+The purpose of this tutorial is to show how it is possible to train YOLOv7 to recognize **American Sign Language letters**. YOLOv7 is an object detection algorithm. Although closely related to image classification, object detection performs image classification on a more precise scale. Object detection locates and categorizes features in images.
 
 ![image](images/overview-notebook.png){.thumbnail}
 
@@ -67,7 +67,7 @@ ovhai data upload <region> asl-volov7-model
 
 ### Launch and access Jupyter notebook with Miniconda framework
 
-You need to attach a volume if your data is in your OVHcloud Object Storage and you want to use it during your experiment, or if you need to save the results of your work in the object storage. For more information on data, volumes and permissions, see [our guide on data](https://docs.ovh.com/gb/en/publiccloud/ai/cli/access-object-storage-data/).
+You need to attach a volume if your data is in your OVHcloud Object Storage and you want to use it during your experiment, or if you need to save the results of your work in the Object Storage. For more information on data, volumes and permissions, see [our guide on data](https://docs.ovh.com/gb/en/publiccloud/ai/cli/access-object-storage-data/).
 
 If you want to launch it from the [OVHcloud Control Panel](https://www.ovh.com/auth/?action=gotomanager&from=https://www.ovh.co.uk/&ovhSubsidiary=GB), just follow this [guide](https://docs.ovh.com/gb/en/publiccloud/ai/notebooks/definition/).