Neural Network; Machine Learning; Deep Learning; Overfitting; Underfitting; Bias; Variance; Regularization; Data Augmentation; Model Complexity; Epochs; Validation

#11 AI: Fixing the Training gone Wrong

Building on Paper #10’s AI training pitfalls—underfitting (too lazy), overfitting (too rigid), high bias (skewed guesses), and high variance (wild swings)—this paper offers practical fixes for our smell detector. We explore three levers: boosting network capacity, extending training with more epochs, and enriching data for smarter learning.