Designed and Managed By PawanKrGunjan

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Data Collection: Raw data is gathered.
Data Preparation: The data is cleaned and transformed into a usable format.
Choosing a Model: Selecting an algorithm based on the nature of the data and task.
Training the Model: The model is exposed to training data, learns patterns, and makes predictions.
Evaluation: The model's performance is tested using new data.
Tuning: Adjustments are made to improve accuracy and efficiency.

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