In this project, I predict air quality index of a city in China using a long short term memory neural network (which works the best for time series analysis).
To get started, you can refer to my notebook. I perform in-depth exploratory data analysis and visualizations to help understand and prove the insights obtained. The dataset contains the data starting from January 1, 2013 to February 28, 2017.
It encompasses the concentrations of different pollutants for each hour of the day along with the data of the environmental conditions. Pollutants include PM2.5, PM10, SO2, NO2, CO, O3. Environmental conditions include temperature, pressure, dewpoint, rain, wind directon and wind speed per minute.
Also, I have just displayed the first 5 entries of all the output arrays and lists. The reason I did so was I didn't want you to scroll through a massive number of entries.