Model: 2 neurons

The first fictional neural network was created with the goal of predicting whether a table was round or not without seeing it, using only its area and radius, and without needing to know geometry

Choose a random area and radius of a table and see for yourself whether it is round or not

Architecture:

• Framework used: PyTorch
• Modelo: MLP con dos neuronas
• Strategy: Custom algorithm for learning rate adjustment
• Hardware: Entry-level GPU (NVIDIA GTX 1050 2GB), training optimized for efficiency

Questions:

• Why doesn't the machine have total precision?
• Why can't the machine predict what's in the box if the tables have a radius greater than 50 cm or less than 20 cm?
• What would happen if the machine had 4 neurons instead of 2?