The dataset used to train the proposed methodology is Air Quality Data in India (2015-2020), taken from publically available sources Kaggle. The dataset includes information on the AQI and air quality at different stations in numerous Indian cities at hourly and daily intervals. The accuracy has...
More importantly, the two systems of vision-based prediction and air quality monitoring will be explicitly integrated to generate an overall (and discrete) cleanliness level.Availability of data and materials The current version of the custom dataset generated during the study is available in the ...
Business does not have a defined use-case for the data at the moment, but they know for sure they want to migrate away from SAS to another system. The SAS files are large and on a local server (on-premise). They want to make sure the data is formatted and migrated to the cloud fo...
, look back for a window of days history, calculating the median 2:00 PM2.5 readings from aotizhongxin in that window. You do this median calculation exercise for a bunch of different window sizes to obtain a bunch medians. The median value of those medians is used as the prediction....
Plant seedlings (Giselsson et al., 2017) RGB Ground fixed platform 407 Image level https://vision.eng.au.dk/plant-seedlings-dataset/ Grass-Broadleaf (dos Santos Ferreira et al., 2017) RGB UAV >10,000 Patch level https://www.kaggle.com/fpeccia/weed-detection-in-soybean-crops Sugar ...
(4D) aspect of the density path. In addition, there was a predictor for each path partition, which encompassed an NN-based learning cell. Each exclusive learning cell was trained by a set of related paths, and each paths set included the related prediction model. According to the obtained ...
, look back for a window of days history, calculating the median 2:00 PM2.5 readings from aotizhongxin in that window. You do this median calculation exercise for a bunch of different window sizes to obtain a bunch medians. The median value of those medians is used as the prediction....
To help hosts set competitive prices and improve their occupancy rates, accurate prediction of Airbnb prices is crucial. In this project, we aimed to predict the price of Airbnb listings in New York City using Ensemble Learning techniques on a Kaggle dataset. Our goal was to train and tune ...
You do not have to use the entire dataset, just use what you need to accomplish the goal you set at the beginning of the project. World Temperature Data: This dataset came from Kaggle. You can read more about it here. U.S. City Demographic Data: This data comes from OpenSoft. You ...
About Dataset This dataset contains ranked air quality measurements for various cities in the world, providing insights into pollution levels across different months of the year. Each entry includes the city name, its rank based on average pollution levels, and monthly average pollution measurements ...