DevPy| Chasers of the Lost Data

Project Details

The Challenge | Chasers of the Lost Data

Help find ways to improve the performance of machine learning and predictive models by filling in gaps in the datasets prior to model training. This entails finding methods to computationally recover or approximate data that is missing due to sensor issues or signal noise that compromises experimental data collection. This work is inspired by data collection during additive manufacturing (AM) processes where sensors capture build characteristics in-situ, but it has applications across many NASA domains.

Data Cauldron

The solution for AI Developer to solve the problems of missing data

DevPy

We are building a web application to help AI Developer to impute data simply by inputting the dataset into our website and the web application will provide an insight to the missing value and predict the missing value by using the existing data.

For now we use these resources:

1. Jupyter Notebook as a platform to run python code. We are using this to first analyzing the multiple dataset to be imputed.

2. Datasets for analyzing are taken from data.nasa.gov

3. We also using stackoverflow to solve certain problems


In future:

1. We might extend our research to make our imputation model more precise and accurate

2. We will develop a full-working website application. (for now we only have prototypes and a few model that we built)

Slide link : https://docs.google.com/presentation/d/1P23c-kchac...

Github repo : https://github.com/muhdlaziem/spaceapps-challenge....