Project name: Student Academic Performance
- The purpose of this project is to learn how to use libraries such as Tensorflow and Pytorch and the like in order to predict students' grades according to a set of their characteristics during an academic semester. For training and evaluation, the Student's Academic Performance dataset is available to you. This selected data has three separate labels for the score. In the given dataset, the class column indicates the grade that has the value of H, M, or L. Other information related to this data can be obtained in the relevant link.
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Neural network implementation:
- Building the Models using Tensorflow library
- Fully connected layers are used only
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Training the Implemented Model:
- In this part, the implemented algorithm should be trained on the training data
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Evaluation of the Trained Model:
- After tarining step, the accuracy and loss should be computed to evaluate the performance of the model
This project was done as a project of Deep Learning course at University of Guilan in May 2022.