Perfecting Neural Network Decision Boundaries for real-life implementation in rural NorCal

Since my AI/ML professional certificate project through the UC Berkeley Emeritus Program, I I've been exploring decision boundaries in non-linear datasets using scikit-learn's make_blobs to create synthetic datasets. 

Post-training, I use the trained models to classify points in a meshgrid, plotting these to visualize the non-linear decision boundary. This exercise highlighted the neural network's ability to handle complex data separations, providing a clear, practical example of advanced machine learning concepts that I will pass on to my students and clients.