👉 The conditioning project is an initiative aimed at enhancing the effectiveness of machine learning models by systematically adjusting their parameters to better fit the specific characteristics of a given dataset. This involves iteratively training and evaluating the model on various subsets of data, applying techniques such as regularization, dropout, or weight decay to prevent overfitting, and fine-tuning hyperparameters to optimize performance. The goal is to create a model that generalizes well to new, unseen data, improving its accuracy and robustness across different scenarios.
