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Adeyemi Akinlawon's Projects

ensemble-techniques-easyvisa icon ensemble-techniques-easyvisa

Analyze the data of Visa applicants, build a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa status recommend a suitable profile for the applicants for whom the visa should be certified or denied.

model-tuning-renewind icon model-tuning-renewind

The objective is to build various classification models, tune them and find the best one that will help identify failures so that the generator could be repaired before failing/breaking and the overall maintenance cost of the generators can be brought down.

python-visualizations-foodhub icon python-visualizations-foodhub

This project sought to analyse the data of different orders made by registered customers on the online portal of a food aggregator company. The analysis would draw some actionable insights and recommendations for the business with the aim of improving it.

statistical-analysis-e-news-express icon statistical-analysis-e-news-express

This project used statistical analysis, a/b testing, and visualization to decide whether the new landing page of an online news portal (E-news Express) is effective enough to gather new subscribers or not. The dependence of conversion on the preferred language will also be analysed on this project.

supervised-learning-booking-cancellations-innhotels icon supervised-learning-booking-cancellations-innhotels

The aim is to analyze the data of INN Hotels to find which factors have a high influence on booking cancellations, build predictive models(logisitic regression, decision trees) that can predict which booking is going to be canceled in advance, and help in formulating profitable policies for cancellations and refunds.

supervised-learning-linear_regression-recell icon supervised-learning-linear_regression-recell

Analyze the used devices dataset, build a model which will help develop a dynamic pricing strategy for used and refurbished devices, and identify factors that significantly influence the price.

unsupervised-learning-trade-ahead icon unsupervised-learning-trade-ahead

Analyze the stocks data, grouping the stocks based on the attributes provided, and sharing insights about the characteristics of each group.

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