Predicting pollution level with an LSTM model
Abstract
This project was done as as an end-of-course project for the "Machine Learning systems for Data Science" course of the Master Degree in Digital Humanities and Digital Knowledge of the University of Bologna, held by professors Stefano Lodi and Elisabetta Ronchieri.
The purpose of the project is to replicate the work process used for the case study in the research paper "Prediction of air quality in Jakarta during the COVID-19 outbreak using long short-term memory machine learning" by Wihayati and F W Wibowo 2021 IOP Conf. Ser.: Earth Environ. Sci. 704 012046.
The data used in the project was provided by the professor and the links to the data source and other information about the project can be found on the project repository.
The purpose of the project is to replicate the work process used for the case study in the research paper "Prediction of air quality in Jakarta during the COVID-19 outbreak using long short-term memory machine learning" by Wihayati and F W Wibowo 2021 IOP Conf. Ser.: Earth Environ. Sci. 704 012046.
The data used in the project was provided by the professor and the links to the data source and other information about the project can be found on the project repository.
Related Hyper-Links
Key Learnings
Building & Training ML Model
Python
Documentation
Tensorflow
Univariate Prediction
Data Cleaning
Data Analysis
Visualising training loss
