References

Below are useful links for machine learning and predictive modeling topics.

Machine Learning Packages

1. scikit-plot: package to build several plots not yet supported on sklearn like ks, cumulative gain and lift plots.
2. feature-engine: package for feature engineering within sklearn pipelines.
3. XuniVerse: calculates information values (IV) and weights of evidence (woe)
4. OptBinning: scorecard development
5. PyCaret: automl package

Machine Learning Courses

1. Machine Learning: Andrew Ng
2. DTona - Canal Téo Me Why: aplicação de machine learning como ela é na vida real, saindo desde a construção da analytical base também até por o modelo em produção.
3. Kaggle Learn

Books

1. Python Data Science Handbook
2. Python for Data Analysis
3. Statistical Inference via Data Science

Churn and Propensity Modeling

1. Predict Customer Churn (the right way) using PyCaret
2. Dataiku Use Case: Churn Prediction
3. Predicting Super Customers using Feature Labs and PyCaret
4. ComposeML: Predict Next Purchase

Lead Scoring

1. Lead Scoring: o guia definitivo para pontuar seus contatos automaticmaente
2. A sofisticação do Lead Scoring com Data Science
3. Predict Lead Score (the right way) using PyCaret