Bandersnatch Monster Cards

Business Value

• Created a Landing Page (as a lead magnet) to drive sales of Monster Cards - 52 card deck playing cards.

What this is:

• Order a 52 card deck of Monster playing cards with more rare monsters as highest value. Ex a very rare Dragon might be the Ace of Diamonds.
• Originally, this was a Bloomtech Labs Data Science project centered on regression to predict Monster rarity.

See it

Demo	Landing Page

Code Example: How to run this Flask app

\```python
function sayHello() {
    console.log("Hello, World!");
}
\```

Tech Stack

• Logic: Python 3.8
• API Framework: Flask
• Templates: Jinja2
• Structure: HTML5
• Styling: CSS3
• Database: MongoDB
• Graphs: Altair
• Machine Learning: Scikit-learn
• Demo App Hosting: Replit.com
• Database Hosting: MongoDB.com
• Landing Page Hosting: Carrd.co

Demo Pages by URL

• /: Home Page
• /data: Tabular Data
• /view: Dynamic Visualizations
• /model: Interactive Machine Learning Model

Development Tickets

1. Sprint 1: Database Operations - Loom Video
   • Develop a database interface class
   • Create random data
   • Populate the database with at least 1000 datapoints
2. Sprint 2: Dynamic Visualizations - Loom Video
   • Notebook exploration of charts
   • Chart function
3. Sprint 3: Machine Learning Model - Loom Video
   • Notebook exploration of scikit-learn data models
   • Machine Learning interface class
   • Model serialization (save and open)
   • Model integration
4. Sprint 4: Deployment - Loom Video
   • Deploy Demo to Replit
5. Sprint 5: Landing Page - Loom Video
   • Create Landing Page on Carrd.co
   • Add AI created Monster images

Development Challenges

1. Sprint 1:
   • Initial project setup:
2. Sprint 2:
   • df
3. Sprint 3:
   • sdf
4. Sprint 4:
   • sdf
5. Sprint 5:
   • sfd

General Development Procedure

1. Fully understand the requirements. Try to delete dumb ones.
2. Explore new libraries, methods in Google Colab Notebooks.
3. Write psuedocode comments of what I'm trying to accomplish.
4. Write class method minimal interfaces and attributes.
5. Write Pytest cases for those methods and attributes.
6. Code.
7. Iterate.

Further Improvements

"Without continual growth and progress, such words as improvement, achievement, and success have no meaning." – Benjamin Franklin

Here's what I would like to improve.

1. Better docstrings for the Machine class (docstrings in the Database class are textbook!)

Keywords

Python 3.8, Flask, Jinja2, HTML5, CSS3, MongoDB, Altair, Scikit-learn, Replit.com, MongoDB.com, Carrd.co

Environment variable

BONUS! Potential Expansions in Business Value

1. Unique Monster Battle Card Game: Magic into being rules for a game where Monsters fight in armies as cards held in decks by players doing battle with one another. With magical attack, swords, armor and keeping track of health points and mana.
2. New Card Games: Expand to other standard card games: Monster Go Fish, Monster Pinochle, etc.
3. Digital Collectibles: Digital card images with downloaded NFTs to ensure uniqueness and rarity.
4. Real Item Collectibles: Printed cards with embedded RFID chips with noncopyable NFTs in them.
5. White Label Platform: Convert into a white label platform for creators to use to create card decks with any theme of AI created images and/or text on them.

Credits and Thanks

Credit goes to:

• 👏 Robert Sharp who created MonsterLab which is the basis for this project.

Credit also goes to the Bloomtech team who made the original version of this project for students

• 👏 April Fairweather: Database Engineer
• 👏 Thackery Binx: Data Analyst
• 👏 Eugene Albright: Machine Learning Engineer

Thanks goes to:

• 👏 Royce Roberts at Bloomtech for his help.