Peter's Picnic

Inspiration

Based on everything I learned in the Udacity AI Nanodegree

What it does

Right now it uses Resnet50 (could change) with some extra layers to detect the right category

How I built it

Mostly build in Jupyter Notebook. Model fitting is run on AWS GPU instances

Challenges I ran into

As with all data problems: getting the data formatted correctly for the deep learning network. I will improve on that for new submissions.

Accomplishments that I'm proud of

It works fairly well :-)

What I learned

Use the "academic" knowledge for a real problem. I love that.

What's next for Peter's Picnic

There's lots of ways this can be improved. But I want to know a baseline score.

Built With

• keras
• python
• tensorflow