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Fix formatting in model training process description
Removed unnecessary spaces before colons in the training process steps.
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theory.md

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@@ -936,11 +936,9 @@ Saving the weights learned by a model mid training for long running processes is
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**Can you tell us how you approach the model training process? ‍⭐️**
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Data Preparation :- Clean the data, scale features, and split it into Train, Validation, and Test sets. After this, choose the architecture & hyperparameters for the model.
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Train & Monitor :- Run forward passes, compute loss, and update weights via backpropagation while tracking both training and validation loss.
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Tuning & Regularization :- Adjust hyperparameters and apply Dropout, Weight Decay, or Early Stopping to prevent overfitting. Then, evaluate the final model on the unseen test set to check real-world performance.
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- Data Preparation: Clean the data, scale features, and split it into Train, Validation, and Test sets. After this, choose the architecture & hyperparameters for the model.
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- Train & Monitor: Run forward passes, compute loss, and update weights via backpropagation while tracking both training and validation loss.
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- Tuning & Regularization: Adjust hyperparameters and apply Dropout, Weight Decay, or Early Stopping to prevent overfitting. Then, evaluate the final model on the unseen test set to check real-world performance.
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<br/>
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