Improving Extreme Weather Forecasts Using AI
This Omdena Local Chapter Challenge runs for 6 weeks and is a unique experience to try and grow your skills in a collaborative and safe environment with a diverse mix of people from all over the world.
You will work on solving a local problem, initiated by the Omdena Silicon Valley, USA Chapter.
In this 4-week project, the team will model data to predict the arithmetic mean of the maximum and minimum temperature over the next 14 days for each location and start date for longer-term weather forecasting to help communities adapt to extreme weather events caused by climate change.
Various Machine Learning methods can be used to make these predictions, such as Random Forests, XGBoost, and Convolutional Neural Networks (CNNs). The team will explore several choices.
Data can be augmented with meteorological data such as temperature, wind speed, and vapor pressure from National Oceanic and Atmospheric Administration (NOAA).
One of the key challenges will be to choose a subset of appropriate features that impact a weather forecast’s predictions to be used in model training.
The goals of this challenge are:
- Data Collection and Exploratory Data Analysis
- Feature Extraction
- Model(s) Development and Training
- Evaluate the best Model
Why join? The uniqueness of Omdena Local Chapter Challenges
Omdena Local Chapter Challenges are not a competition or hackathon but a real-world project that will grow your experience to a new level.
A unique learning experience with the potential to make an impact through the outcome of the project. You will go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.
And the best part is that you will join the global and collaborative community of Omdena with tons of benefits to accelerate your career.