Machine Learning and AI concepts can be intimidating for a lot of people unfamiliar with the math and science behind it. I felt I could make a few machine-learning tools online which could be accessed by anyone with a phone or a desktop browser to solve real-world problems.
What it does
It enables anyone with internet access to use machine learning tools to solve tasks related to the environment and beyond, right from their browser. It's an aspirational platform that aims to be a hub for machine learning models for environment-related tasks.
How I built it
Challenges I ran into
Training using a self-collected dataset. This was done as a proof of concept exercise with results pointing towards an easy path for implementation by the public in the future.
I ran into hurdles trying to get p5.js working alongside the ml5.js libraries but finally overcame it using their docs and StackOverflow.
Accomplishments that I'm proud of
Implementing and running machine learning models on the browser resulting in a project that can be potentially scaled in the future. This can potentially be useful to people with low internet access in many developing countries.
What I learned
What's next for Environment AI
Build a production-grade platform to enable people to contribute to the growing list of machine learning tools.
Write docs to enable people to train their environment-specific machine learning models and share them with the rest of the community.
Find ways to make the models run offline. This could be really useful for people in developing countries with limited access to the internet.