• This project was inspired in light of a recent international event, which was the highly-anticipated SpaceX and NASA combined mission
  • This project served as a stepping stone for furthering my interest in technology and aerospace, in order to thoroughly understand these two inter-related fields, along with continuing humankinds' endeavours in the fields of technology and aerospace.

What it does

  • This system/algorithm identifies the stages of space flight, specifically the flight to orbit stages, that the spacecraft undergoes.

How I built it

  • Tensorflow libraries
  • Google Colab notebooks
  • Python

Challenges I ran into

  • GPU's setup
  • Finding training and testing data
  • Achieving a high accuracy rate in the algorithm

Accomplishments that I'm proud of

  • Having a high accuracy rate (90%) for the machine-learning algorithm, with the given training and testing data

What I learned

  • Understanding the technical aspects of Tensor flow libraries and Google Colab notebooks
  • This was done through following tutorials, along with asking help from mentors, in order to develop this interactive platform

What's next for Out of this World!

  • Providing more training data such as image datasets of additional companies and agencies in the field of space exploration, other than SpaceX and NASA
  • Reducing the limitations in the algorithm (e.g. identifying spacecraft from a wide range/variety of companies and agencies)
  • Collaborating with educational platforms (e.g. Khan Academy, Udemy, and Skillshare) to teach others about and introduce them to the field of space exploration, specifically the phases needed in the flight to orbit process

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