cpu only

Author: cmanzo

docker/README.md

@@ -1,4 +1,4 @@
-# Deep Learning Crash Course
+# Deep Learning Crash Course Docker Image
 
 [![Early Access - Use Code PREORDER for 25% Off](https://img.shields.io/badge/Early%20Access%20Now%20Available-Use%20Code%20PREORDER%20for%2025%25%20Off-orange)](https://nostarch.com/deep-learning-crash-course)  
 by Benjamin Midtvedt, Jesús Pineda, Henrik Klein Moberg, Harshith Bachimanchi, Joana B. Pereira, Carlo Manzo, Giovanni Volpe  
@@ -10,4 +10,54 @@ ISBN-13: 9781718503922
 
 ![Docker Image CI](https://github.com/DeepTrackAI/DeepLearningCrashCourse/actions/workflows/docker-publish.yml/badge.svg)
 
+A ready-to-run JupyterLab environment with all notebooks and dependencies baked in.  
+Works on Intel & Apple-Silicon Macs, Linux ×86_64 & ARM64.
+
+---
+
+## Prerequisites
+
+- [Docker Desktop](https://www.docker.com/products/docker-desktop) (macOS, Windows) or Docker Engine (Linux)  
+- (Optional) [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/) on Linux for GPU support  
+- (Optional) VS Code + [Dev Containers](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers) extension
+
+
 ---
+## General use
+
+### 1. Pull the latest image
+
+```bash
+docker pull ghcr.io/deeptrackai/deep-learning-crash-course:latest
+```
+Docker will automatically select the correct architecture slice (amd64 or arm64).
+
+### 2. Run JupyterLab
+```docker run --rm -it \
+  -p 8888:8888 \
+  -v "$(pwd)":/home/jovyan/work \
+  ghcr.io/deeptrackai/deep-learning-crash-course:latest
+  ```
+After startup you’ll see a URL with a token (e.g. http://127.0.0.1:8888/lab?token=…). Paste it into your browser.
+
+--- 
+
+## Use in VS Code (Dev Containers)
+
+### 1. Install the “Dev Containers” extension in VS Code.
+
+### 2. Command Palette → Dev Containers: Open Folder in Container…
+
+### 3. Select your local DeepLearningCrashCourse folder.
+
+### 4. In the new window:
+
+   - Install Python & Jupyter extensions when prompted.
+
+   - Open Folder → /home/jovyan/work (the repo inside the container).
+
+   - Select Interpreter in the bottom bar → the one at `/opt/conda/bin/python` (Python 3.11).
+
+### 5. Use the integrated terminal (`Ctrl`+``) or Run & Debug scripts (F5).
+
+### 6. Open any `.ipynb` and run cells.