Project Proposal Document:

o Introduction: Briefly describe the dataset and its source.

o Problem Statement: Define the problem you intend to solve using a basic neural

network.

o Objectives: Outline the goals and objectives of your project.

o Proposed Methodology: Describe the type of neural network you plan to use and

why it is suitable for the problem.

Then perform the following $-$

Select a simple dataset from reliable sources like UCI Machine Learning

o Then Clean the dataset $($handle missing values, outliers, etc.$).$

o And Perform basic data normalization or standardization if required.

o Conduct EDA to understand the dataset$$s characteristics.

o Visualize important features and relationships within the data.

o Then document the preprocessing steps and EDA findings.

Define the architecture of your basic neural network $($e$.$g$.,$ number of layers,number of neurons per layer, activation functions$).$

o Implement the neural network model using MATLAB$$s Neural Network Toolbox.

o Ensure your code is well$-$structured and commented.

o Train the neural network on a subset of the data to ensure it is working correctly.

o Address any initial issues or bugs in the implementation.

o Train the neural network on the full dataset.

o Use simple techniques to prevent overfitting, such as adjusting the number of training epochs.

o Evaluate the model$$s performance using basic metrics