Download the Dataset and Copy the Code from Here - [ Ссылка ]

The ability of prediction is a powerful skill. If we could predict tomorrow, we would know exactly what to do today to make the tomorrow better. For example, if you would know the score a student is going to make before attending the exam, you could suggest him some effective way to make his scores better. In this tutorial, we are going to learn one such approach – Performance of Students Prediction using Deep Neural Network. After completing this tutorial, you will be able to design, construct, train and use your own deep neural network to predict the performance of the students. Let’s get started.

The Steps of Implementation:
The concept of this tutorial has been implemented in MATLAB using the following 7 steps:
1. Loading the dataset,
2. Specify the training and testing data,
3. Design the and construct the network,
4. Split data into training, testing and validation dataset to train the network,
5. Train the network,
6. Test the network by passing some arbitrary or testing data.

Dataset:
You can download the dataset used in this tutorial from here – [ Ссылка ]

MATLAB Code:
The MATLAB code using this tutorial are here. You are free to copy the code and use where ever you want. Three functions were created to implement the students’ performance predictor. They are:
1. Load Data – to load the dataset and separate the training and target data.
2. Train Network – to construct and train the network.
3. Test Network – to test the network.

You can copy the code from here - [ Ссылка ]

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