Write a service which can analyse user data and predict the accuracy and user interestes.
•Clean and pre-process the data, converting categorical variables into a format suitable for machine learning models.
• Decide which features (e.g., lead source, industry, time since last contact) to include in the model.
• Split the data into training and testing sets.
• Train each model (decision tree, random forest, logistic regression, neural network) on the training data.
• Evaluate each model's performance using metrics like accuracy, precision, recall, and the area under the ROC curve.
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