[Nomination] ABDULSALAM YAZID BANDE #273
Description
Select one:
- I am nominating myself for the PyTorch Ambassador Program.
- I am nominating someone else to become a PyTorch Ambassador.
Please confirm that the nominee meets the following requirements:
- The nominee is 18 years of age or older.
- The nominee agrees to abide by the PyTorch Code of Conduct.
- The nominee agrees to comply with the Linux Foundation Antitrust Policy.
- The nominee meets at least one of the qualifications listed in the PyTorch Ambassador Program Requirements.
Nominee Name
ABDULSALAM YAZID BANDE
Nominee Email
Nominee's GitHub or GitLab Handle
https://github.com/abdulsalam-bande
(Optional) Organization / Affiliation
No response
City, State/Province, Country
Istanbul, Turkey
Your Name
No response
Your Email (Optional)
No response
How has the nominee contributed to PyTorch?
- An active contributor to PyTorch repositories (e.g., commits, PRs, discussions).
- A speaker at PyTorch events or workshops.
- A PyTorch user group organizer or meetup host.
- A researcher or educator using PyTorch in academic work or training.
- An active leader in the PyTorch community with at least one year of experience in:
- Organizing events (virtual/in-person).
- Speaking at AI/ML conferences.
- Mentoring others in PyTorch.
- Creating technical content (e.g., blogs, videos, tutorials).
🏆 How Would the Nominee Contribute as an Ambassador?
Note: I previously submitted an incomplete version (now closed)—please consider this as my final and complete application. For better readability, you may paste it into a text editor.
1. Knowledge-Sharing & Content Creation
As an ambassador, I’ll continue the PyTorch education work I began in 2020. On YouTube, I break down PyTorch’s neural network modules using pen and paper, walking through them step by step. My goal is to help researchers and beginners understand both the intuition and mechanics behind common layers and architectures.
I aim for each PyTorch module to have a corresponding video that is simple to understand. This project is still ongoing, and I’ve already covered most major modules, including those used in generative models. My next focus will be on PyTorch’s reinforcement learning modules.
2. Increasing Access to ML Education Through PyTorch
I want to help students see how the math they learn in school connects to machine learning and eventually to real-world applications.
For example, torch.nn.Linear is the foundation of many important components in architectures like transformers. Exploring how the Linear Layer works can inspire ideas for more efficient or lightweight alternatives. That kind of curiosity and experimentation is exactly what PyTorch enables.
To support this, I plan to collaborate with schools, tech hubs, and learning communities to deliver beginner-friendly lectures and hands-on workshops. These sessions will introduce PyTorch from the ground up with no prior programming or ML experience required.
3. Hosting Workshops & Events
While my outreach in schools focuses on foundational exposure, I also plan to run more structured workshops for learners looking to deepen their understanding of PyTorch and ML.,
I’ll organize both online and in-person events, depending on the needs of each community. These workshops will be:
• Topic-specific, focused on deep dives into key PyTorch and ML concepts—for example:
o Selecting a layer from PyTorch’s documentation and walking through how it works in detail
• Project-based and interactive, helping participants gain hands-on experience through guided coding exercises
• Open to all, but particularly valuable for those who already have basic familiarity with Python or ML and want to grow their skills
The goal is to bridge the gap between beginner knowledge and real-world ML application by showing how concepts translate into working models using PyTorch.
Many software developers today use generative models like those from OpenAI without fully understanding the underlying technology. My workshops will also target these developers by offering them a clearer view of how the tools they use actually work under the hood.
4. Mobile App for Learning PyTorch
I believe large language models can help us build powerful learning tools more efficiently than ever. In addition to my upcoming mobile app Berry, which focuses on health management, I plan to develop a mobile companion app for learning PyTorch. The app will feature
• Interactive flashcards on PyTorch modules
• Code examples and model visualizations
• Quick daily challenges like “build a model in 5 minutes”
This will help make PyTorch education more fun and accessible—right from a phone. It could also be useful for children using iPads, essentially exposing them to PyTorch at an even earlier stage.
5. Contribution to the PyTorch Ecosystem
While education is my strongest area, I also plan to contribute directly to the PyTorch ecosystem by:
• Submitting PRs for small bug fixes or documentation improvements on GitHub
• Extending PyTorch tutorials, especially in reinforcement learning, based on what I’m building and teaching.Any additional details you'd like to share?
- PyTorch YouTube Channel : https://www.youtube.com/@machinelearningwithpytorch/featured
- Website: https: https://abdulsalam-bande.github.io/BandeLab/
- Google Scholar: https://scholar.google.com/citations?user=OlrA3O8AAAAJ&hl=en
- Mobile Application (Berry): https://www.youtube.com/watch?v=85bk4oybVKs
- Resume : https://drive.google.com/file/d/1cCD4qCeIcoW6vcOhdDP8HW3MshFIcaDJ/view
- Pytorch Developer Forum : https://discuss.pytorch.org/u/abdulsalambande/summary