Data visualization
Data visualization in neural networks involves using graphical techniques to represent data and model performance. It helps users understand how the network operates and makes decisions by presenting key metrics in a visual format. By visualizing metrics like loss and accuracy during training, users can monitor the model’s learning progress and detect issues like overfitting, where the model performs well on training data but poorly on new data. Data visualization tools can also illustrate the network’s architecture, showing the layers and neuron connections, providing a clearer view of the model’s structure and complexity. This makes it easier to analyze and optimize the neural network.
This software is researched and edited by
Rajat Gupta is the founder of Spotsaas, where he reviews and compares software tools that help businesses work smarter. Over the past two years, he has analyzed thousands of products across CRM, HR, AI, and finance — combining real-world research with a strong foundation in commerce and the CFA program. He's especially curious about AI, automation, and the future of work tech. Outside of SpotSaaS, you'll find him on a badminton court or tracking the stock market.
Disclaimer: This research has been collated from a variety of authoritative sources. We welcome your feedback at [email protected].
