ML Pipeline for weather forecasting
Automated weather forecasting pipeline for PM2.5 levels in Rotterdam
Machine LearningFeature EngineeringPipeline
Challenge
Automating the creation and updating of a ML predictor model based on sensor data for predicting PM2.5 levels in Rotterdam.
Approach
Creating a pipeline that creates features from sensor data and trains a regression model using PyTorch, which is updated every day to predict the next week's PM2.5 levels.
Impact
Create a webpage that displays the predicted PM2.5 levels in Rotterdam, with a live update every day.
Tech Stack
PythonPyTorchHopsworks