Analyse the datasets and build a Machine Learning model

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Analyzing datasets and building a Machine Learning model for Associate Data Scientist role.

1. Explore and understand the datasets to identify patterns and relationships.
2. Preprocess the data by handling missing values, encoding categorical variables, and scaling numerical features.
3. Split the data into training and testing sets for model evaluation.
4. Choose a suitable Machine Learning algorithm based on the nature of the problem (classification, regression, clustering, etc.).
5. Train the model on the training data and evaluate its performance using metrics like accuracy, precision, recall, and F1 score.
6. Fine-tune the model by adjusting hyperparameters and optimizing for better performance.
7. Finally, test the model on the unseen testing data to assess its generalization ability.

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