Not just Dataset
There is collected information from the university's daily services. All tasks contribute to log data and are stored in the database. For example, students enrol in courses each semester. Teachers submit their learning/teaching records in the grading system. Researchers update their scholar funding to research monitoring. The connection or linkage between databases improves their performance with the data-driven concept. This is the input of the next process.
Dataset Visualisation Detail
Data is essential for solving a particular problem, whereas a dataset is data for ML processing. It starts with collecting the existing database, preprocessing with the testing question, and annotating selected features to get the completed prediction. This is the process of transferring the data into a document or application. It reduces the time consumption of modelling all the data from every level based on the required Dataset.
Data will be divided into learning and testing data. It uses different algorithms to find the most suitable solution that gets a good prediction. For example, the classification uses linear regressing, logistic regression, or decision trees that work with supervised learning. Thus, clustering supports unsupervised, semi-supervised, or reinforcement learning.
Firstly, the algorithm(model) uses the remaining 30% of the Dataset to test and predict the results. ML introduces the classifier algorithms for training the dataset model from variables and predictors. However, feature extraction to reduce the number of existing features also reduces the time consumption of the ML. Testing is the process of completing the question.
rajabhat Ai daily
Rajabhat University develops this dataset and uses it for creating and sharing between the universities. It also operates in the data analysis to predict the crucial knowledge to improve the quality of community life. This is the first data collaboration of Rajabhat University as open data website.
free dataset download
delivered dataset a week
This research is mainly based on how to build the Dataset for Rajabhat University with the existing database and transform it into a dataset. At the end of this research, it contributes two knowledge innovations: “Which existing databases are suitable to develop the Rajabhat Dataset?” and “How to use AI for analysis of Rajabhat Dataset?”