Answer / Ajay Pratap Singh

To debug a machine learning model that is not performing well, you can start by visualizing the data distribution and checking for any anomalies or biases. Investigate the performance on validation sets, and compare the predicted results with actual values to identify patterns of misclassification or regression errors. Check the model's hyperparameters, including learning rate, regularization strength, and batch size, as well as the choice of optimization algorithm. Lastly, consider using techniques like cross-validation and ensemble methods to improve model robustness.

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