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Local Chapter project

Silicodata Science for Climate Change: Mitigate Greenhouse Gases Emissions by Reducing Energy Consumption of Buildings

Unsupervised LearningReinforcement LearningEDAAnomaly DetectionPredictive Analytics
Start date
January 27, 2022
Finish date
February 19, 2022
Project status
completed
Silicodata Science for Climate Change: Mitigate Greenhouse Gases Emissions by Reducing Energy Consumption of Buildings

Goal of the project

Exploring ways to reduce the energy consumption of buildings. The team will analyze regional differences in building energy efficiency, and build models to predict building energy consumption, an important first step in understanding how to maximize energy efficiency. Accurate predictions of energy consumption can help policymakers target retrofitting efforts to maximize emissions reductions

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What to expect from a Local Chapter project

First project

  • Welcomes beginners and experienced practitioners.
  • Focuses on education and collaborative delivery.
  • Produces open-source project work.

Benefits

  • Address a significant real-world problem with your skills.
  • Build your project portfolio.
  • Demonstrate your work to organizations and project partners.

Requirements

  • Working English communication.
  • A learning mindset.
  • Commitment to collaborative project work.

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