This dataset provides insights into the long-term health conditions experienced by individuals who have recovered from Covid-19. Collected between September 2022 and March 2023 in Erbil, Kurdistan Region of Iraq, the dataset encompasses 3060 observations with 36 features and 9 target variables.
The "Employee Information" dataset is a collection of information about employees working in communication and construction companies in Kurdistan/Iraq in 2016. The dataset contains 29 features that include personal information, educational information, and working background information. The purpose of this dataset is to provide companies with the necessary information to make decisions about an employee's future working. The class feature is also included in this dataset, which indicates whether an employee deserves a recommendation for promotion or not.
The dataset was created by using the Facebook app to gather comments from users. These comments were sourced from various posts on pages about medical topics, as well as news, economy, education, and sports. These comments, which are short pieces of text, were categorized as either positive (medical) or negative (non-medical) for the purpose of text classification. The negative comments make up 55% of the dataset, while the positive comments make up 45%.
This dataset contains a list of nearly 1500 distinct Kurdish words, each word has been repeated 59 times with various handwritings and saved as .jpg files.
This dataset contains a list of over 23000 Kurdish and Arabic names for both genders with multi-fonts.
This dataset provides insights into the long-term health conditions experienced by individuals who have recovered from Covid-19. Collected between September 2022 and March 2023 in Erbil, Kurdistan Region of Iraq, the dataset encompasses 3060 observations with 36 features and 9 target variables.
The "Employee Information" dataset is a collection of information about employees working in communication and construction companies in Kurdistan/Iraq in 2016. The dataset contains 29 features that include personal information, educational information, and working background information. The purpose of this dataset is to provide companies with the necessary information to make decisions about an employee's future working. The class feature is also included in this dataset, which indicates whether an employee deserves a recommendation for promotion or not.
The dataset was created by using the Facebook app to gather comments from users. These comments were sourced from various posts on pages about medical topics, as well as news, economy, education, and sports. These comments, which are short pieces of text, were categorized as either positive (medical) or negative (non-medical) for the purpose of text classification. The negative comments make up 55% of the dataset, while the positive comments make up 45%.
This dataset contains a list of nearly 1500 distinct Kurdish words, each word has been repeated 59 times with various handwritings and saved as .jpg files.
This dataset contains a list of over 23000 Kurdish and Arabic names for both genders with multi-fonts.
