#Propensity Modelling #Data Exploration #ML Interpretability #Model Selection #Optimisation #Machine Learning

Propensity Modelling - Using h2o and DALEX to Estimate Likelihood to Purchase a Financial Product - Abridged Version

In this day and age, a business that leverages data to understand the drivers of customers’ behaviour has a true competitive advantage. Organisations can dramatically improve their performance in the market by analysing customer level data in an effective way and focus their efforts towards those that are more likely to engage. One trialled and tested approach to tease this type of insight out of data is Propensity Modelling, which combines information such as a customers’ demographics (age, race, religion, gender, family size, ethnicity, income, education level), psycho-graphic (social class, lifestyle and personality characteristics), engagement (emails opened, emails clicked, searches on mobile app, webpage dwell time, etc. ...

#Machine Learning #Propensity Modelling #ML Interpretability #Model Selection

Propensity Modelling - Using h2o and DALEX to Estimate the Likelihood of Purchasing a Financial Product - Estimate Several Models and Compare Their Performance Using a Model-agnostic Methodology

In this day and age, a business that leverages data to understand the drivers of its customers’ behaviour has a true competitive advantage. Organisations can dramatically improve their performance in the market by analysing customer level data in an effective way and focus their efforts towards those that are more likely to engage. One trialled and tested approach to tease out this type of insight is Propensity Modelling, which combines information such as a customers’ demographics (age, race, religion, gender, family size, ethnicity, income, education level), psycho-graphic (social class, lifestyle and personality characteristics), engagement (emails opened, emails clicked, searches on mobile app, webpage dwell time, etc. ...

#Machine Learning #Market Basket Analysis #Model Selection

Market Basket Analysis - Part 2 of 3 - Market Basket Analysis with recommenderlab

My objective for this piece of work is to carry out a Market Basket Analysis as an end-to-end data science project. I have split the output into three parts, of which this is the SECOND, that I have organised as follows: In the first chapter, I will source, explore and format a complex dataset suitable for modelling with recommendation algorithms. For the second part, I will apply various machine learning algorithms for Product Recommendation and select the best performing model. ...