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A_Rodionoff

Alexander Rodionov

Recently Published

Making maps using {geokz}-package
Geographic coverages of Kazakhstan at several levels (Country, Oblasts & Cities of Republican Significance, Rayons of Oblasts & City of Oblast Significance)
Using Configuration Sets of Values in R
Использование предустановленных наборов из конфигурационного файла config.yml в R на примере работы с Базой Данных
Simulating COVID-19 Non-Pharmaceutical Governmental Interventions
Stochastic, discrete-time, Individual Contact Model (ICM) from SIR Model Family using package `EpiModel` (https://www.epimodel.org)
Vehicle Loan Default Prediction (Classification Problem)
Using package `MicrosoftML` (Microsoft Machine Learning Server 9.4.7)
R & Python: how to share in 'reticulate' package
R Markdown & Python: Predicting Badrate Assets of the Banking System (using Python package 'numpy', 'pandas', 'scipy' & 'sklearn')
Statistical Methods in Customer Relationship Management. Table of Contents
Statistical analysis in R by SAS examples in the book by Kumar V. and Petersen Andrew J.
Statistical Methods in Customer Relationship Management. Chapter 3. Customer acquisition
Statistical analysis in R by SAS examples in the book by Kumar V. and Petersen Andrew J.
Statistical Methods in Customer Relationship Management. Chapter 4. Customer Retention
Statistical analysis in R by SAS examples in the book by Kumar V. and Petersen Andrew J.
Statistical Methods in Customer Relationship Management. Chapter 5. Balancing Acquisition and Retention
Statistical analysis in R by SAS examples in the book by Kumar V. and Petersen Andrew J.
Statistical Methods in Customer Relationship Management. Chapter 6. Customer Churn
Statistical analysis in R by SAS examples in the book by Kumar V. and Petersen Andrew J.
Statistical Methods in Customer Relationship Management. Chapter 7. Customer Win-Back
Statistical analysis in R by SAS examples in the book by Kumar V. and Petersen Andrew J.
Deep Learning with Keras/Tersorflow (Artificial Neural Network)
Bank Task 1 - Regression Problem on Automatic Pricing of Cars
Ensemble of Machine Learning Algorithms
Bank Task 2 - Classification Problem to identify Fraud in the Customer Base
Machine Learning: Forecast of Table Water Sales
Rolling Cross-Validation of Forecast Models and the Ensemble of them (Jan-Oct 2017)
Bayesian Inference: Install RTools and package ‘rstan’
Как инсталлировать библиотеку `Stan` и начать использовать в R