Fashion Class Classification

Inspiration

Choosing the right design, colors and style to mass produce is often times a decision that can make or break a retailers season or entire year. This fashion branding tool with enable retailers to learn the buying patterns of customers and classify customer's fashion choice by classifying popular styles, colors and design choice.

What it does

The fashion classifier will pull from multiple API (both behind the firewall and on cloud) from multiple suppliers of fabric, zippers, buttons, etc,classify the fabric and material styles and calculate cost of material in real-time based on certain rules that extrapolate how much initial demand will lead to 1) whether that color, style, fabric will make it to production 2) if it does make the final cut for production, how many copies to make.

How I built it

We will use either Tensorflow or Spark to build the fashion classifier. We will enable ARC to pull from suppliers API and check availability and cost of material. We can use HDP to pull data from on-premise and cloud data sources. We can use Corticon as a business rules manager to make the business rules decision on what makes the final cut and how much material to purchase.

Challenges I ran into

Accomplishments that I'm proud of

What I learned

What's next for Breast Cancer Classification

Built With

• api
• python
• tensorflow