Draw architecture diagram for your Machine Learning Project

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Accepted Answer

The architecture diagram for a Machine Learning project typically includes data preprocessing, model training, evaluation, and deployment stages.

Data preprocessing stage involves cleaning, transforming, and preparing the data for model training.
Model training stage includes selecting the appropriate algorithm, training the model on the data, and tuning hyperparameters.
Evaluation stage involves assessing the model's performance using metrics like accuracy, precision, recall, and F1 score.
Deployment stage focuses on integrating the trained model into a production environment for real-world use.
Common tools used in Machine Learning projects include Python, TensorFlow, scikit-learn, and Jupyter notebooks.

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