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Report abuseThis research goal is to build binary classifier model which are able to separate fraud transactions from non-fraud transactions.
Explanate how the algorithm of Expectation-Maximization in Gaussian Mixture works for clustering.
Jupyter Notebook 10
Regression models for predicting customer acquisition costs (CAC) and the effectiveness of univariate and lasso feature selection techniques in improving the accuracy.
Jupyter Notebook
RFM Segmentation and predicting number of purchases made by customers, customer churn rate, forecasted avg transactions of potential sales and customer lifetime value using Beta-Geofitter/Negative β¦
Jupyter Notebook
Recommendation System using Context-Aware Factorization Machine algorithm with Monte Carlo Markov Chain Optimization to predict rating given by user to certain item. Comparing with Content-Based Reβ¦
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