/YapAiTek-Assessment

Predicting weather quality (Pollutant Standards Index or PSI) in Singapore.

Primary LanguageJupyter Notebook

YapAiTek Assessment

This is the assessment of YapAiTek company as a part of the process of selecting candidates for their Junior Data Scientist Position.

This is a time-series forcasting problem. The goal is to predict air quality of Singapore (Pollutant Standards Index or PSI) using an existing dataset of PSI levels between year 2016 to 2019.

Getting Started

You can copy the dataset to your Google Drive and open the jupyter notebook on Google Colab or alternatively, you can run the jupyter notebook locally. In each case, make sure to change the dataset_path variable to the correct path of dataset.

Prerequisites

You need the python 3 and the following packages to run the code.

tensorflow               2.2.0
numpy                    1.18.5
pandas                   1.0.5
matplotlib               3.2.2

About the Task

Dataset

dataset

Model

We used 4 lags of data as the input to a LSTM model.

Results

The following image is the plot of prediction vs true PSI levels for out test data:

dataset

Contributing

Feel free to make issues or create pull requests :)

Author