Inspiration
Massive Covid-19 Supply Chain Issues for Lifesaving Medical Supplies and its tremendous impact on society
What it does
End-to-end data flow solution. It ingests diverse sources of data, transforms them into a common format, and predicts supply chain disruptions using machine learning.
How we built it
Researched open-source data, common challenges for aggregating and transforming data and delays in insights, and then thought about the best way to fix these challenges
Challenges we ran into
Finding appropriate data, formating of different data types, decreasing processing time, minimizing error
Accomplishments that we're proud of
Novel solutions to positively impact medical supply chains predict issues and diverse data ingestion
What we learned
New frameworks, new libraries used, and more understanding of supply chain challenges from background research
What's next for MEDWEB
Continue to decrease the processing time and improve the accuracy of ML model further
Built With
- colab
- gcp
- h2o
- machine-learning
- nifi
- python
- scikit-learn
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