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Cover image for Project: Monetizing TikTok Content with Lightweight ML (Learning in Public)
JR. STEVE JUNIN
JR. STEVE JUNIN

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Project: Monetizing TikTok Content with Lightweight ML (Learning in Public)

Why this project exists

This is not a “get rich fast” project.

I’m experimenting with a simple idea:

can lightweight ML signals help creators understand what content might be monetizable—without chasing hype or vanity metrics?

This project is part of my learning journey, shared openly.


What the project does (at a high level)

The system looks at public TikTok signals, such as:

  • basic engagement ratios (views / likes / comments)
  • posting consistency
  • simple trend patterns over time

Using these, it produces signals, not predictions.

No automation.

No scraping abuse.

No bot behavior.


What this project is NOT

  • ❌ Not financial advice
  • ❌ Not a growth hack
  • ❌ Not a TikTok bot
  • ❌ Not guaranteed monetization

It’s an experiment, not a product.


Tech stack (simple on purpose)

  • Python
  • Basic ML heuristics (no heavy models)
  • CSV / lightweight storage
  • Manual validation

Keeping it small helps me understand every part of the system.


Why I’m sharing this

I come from a small community with limited access to formal tech education.

Sharing progress publicly helps me:

  • learn better
  • get feedback
  • document mistakes honestly

This is learning in public, nothing more.


What’s next

  • Improve signal quality
  • Better data visualization
  • Clear documentation
  • Decide whether this stays a learning project or evolves further

Feedback welcome

If you’ve worked on:

  • content analysis
  • creator tools
  • ML for social platforms

I’d appreciate any constructive feedback or pointers.

Thanks for reading.

`{% details Project status %}
This project is still experimental and under active learning.
Nothing here should be considered production-ready.
{% enddetails %} 
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