For the third challenge of the GDGC x AIC Tech Tournament, you will need to develop your own machine learning model utilizing a Kaggle dataset relating to space. This challenge is all about applying machine learning techniques, data processing, and creative AI approaches.

3 people max.

Requirements:

1. Dataset Access

1. Teams must access a Kaggle dataset that relates to space in some capacity such as planets, constellations, etc.

2. Preprocess the dataset as needed such as resizing images.

2. Model Development

   1. For example, using OpenCV to process a dataset containing images

1. Use any framework for processing the dataset.

2. Train a model using any machine learning framework of your choice such as Tensorflow, PyTorch, etc.

3. Creative Aspect

1. Apply your AI model creatively such as creating a game, animate decision-making, etc.

2. Showcase what your AI model is being used for in a unique way

3. How does your model expand upon the dataset?

Nice to have:

1. Interactive Visualizations

1. Provide displays of model’s predictions such as confusion matrices, solar systems, etc.

2. Real-time predictions

1. Have the model able to receive input and predict its category

3. Deployment

1. Deploy model as a web app or API for public use

Submission: Due: 5 pm

1. A short 1-2 slide presentation for your project

1. “Demo” - screenshots of your classifications OR 30 second video

• DESIGN
  How appealing is your final product? Would it be a great addition to your resume or portfolio?
• TECHNICAL IMPLEMENTATION
  Did you challenge yourself and use technologies you are unfamiliar with? Were you able to successfully learn a new technology and incorporate it into your submission?
• PITCH
  Why is your project the best out of all of them? Convince us that yours deserves to advance to the next round to compete for the title of Tech Champion...
• TOTAL POINTS FOR SUBMISSION
  10 POINTS
• WINNER POINTS
  100 POINTS
• IN PERSON DEMO
  50 POINTS