Explain end to end ML project

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Accepted Answer

End to end ML project involves data collection, preprocessing, model training, evaluation, and deployment.

1. Data collection: Gather relevant data from various sources.
2. Data preprocessing: Clean, transform, and prepare the data for modeling.
3. Model training: Develop and train machine learning models using the processed data.
4. Model evaluation: Assess the performance of the models using metrics like accuracy, precision, recall, etc.
5. Model deployment: Implement the model into production environment for real-world use.
6. Continuous monitoring and optimization: Monitor model performance, retrain if necessary, and optimize for better results.

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