There is a need for an interactive and visual method to illustrate and expand the understanding of neural networks and their functionality. The user wants to have the ability to directly and in real-time visualize the impact of changes in the weights and functions of this network. However, the autonomous learning process suffers, as no tool has been found that manages understanding of important aspects such as complex multi-layer neural networks, workings of gradient descent, hyperparameters, distributions, and overfitting. Moreover, there is a lack of a predictive function that shows how changes affect the performance of the network. In addition, having the ability to experiment with both provided and own datasets would be beneficial for the complete learning process.

Playground AI efficiently addresses the described problem by providing an interactive and visual platform that enables the user to gain a comprehensive understanding of neural networks. The tool specifically shows how changes to weights and functions affect the behavior of the network, and visualizes this in real time. It also covers important aspects such as complex, multi-layer neural networks, the workings of gradient descent, hyperparameters, distributions, and overfitting. In addition, Playground AI allows experimentation with various predefined data sets or the uploading of one's own data. It also includes a prediction function that demonstrates the effects of changes on the performance of the network, thereby promoting deeper understanding. It is therefore an effective tool that helps users to better understand and trace the complexity and dynamics of neural networks.