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What's the problem?
Many learners do not have access to in-depth resources that explain how ANNs function unless they are affiliated with an academic institution or have access to specialized courses and tutorials. This limitation leaves a gap in understanding for individuals interested in learning about ANNs. Traditional learning materials like textbooks, static diagrams, and even online tutorials may provide fundamental knowledge, but they lack the interactive and dynamic elements that bring ANNs to life.
Why VR?
This project proposes an innovative approach to make ANN training more comprehensible by transforming the complex process of training simple ANNs, such as Multi-layer Perceptrons (MLPs) or Convolutional Neural Networks (CNNs), into an immersive, interactive experience. By leveraging VR technologies, users can be placed directly within the network, actively role-playing a neuron, gradient, or activation function. This first-person perspective allows users to visually and physically experience important stages of ANN training, including weight updates, error propagation, and activation function application.
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