How to get noticed more , specially by ML/DL oriented organizations?

[GabiYamato]

Just starting out,
have a good amount of experience in deep learning, but haven't made stuff public yet

[smartjunaid]

@GabiYamato

🔹 Advice for someone starting out with deep learning but hasn’t made projects public yet:

Start small, share early → even small projects or experiments on GitHub help build a public presence.

Document well → clear README, setup instructions, and examples make your work understandable.

Use notebooks → Jupyter or Colab notebooks are great for sharing experiments and results.

Contribute to open-source → fixing bugs, adding features, or sharing models in existing repos builds credibility.

Portfolio mindset → treat GitHub as your professional portfolio; even side projects showcase your skills.

💡 Public contributions + good documentation = others can see and value your expertise, even if you’re just starting. 🚀

[raunak0400]

You can start small — publish some of your deep learning experiments, even if they’re not full projects. A few good starting points:

Share Jupyter notebooks with clear explanations.

Reproduce a well-known paper and document your results.

Open-source utility scripts (data preprocessing, visualization, training helpers).

Write concise READMEs so others can understand and use your work.

Consistency matters more than perfection. Over time, this builds a strong portfolio.

If this answer helps you even a bit, please mark my reply as ‘Answer’. ✅