Pitfalls within Agile Data Science ProjectThere are plenty of reasons why a data science project can fail such as: selection bias, target leakage, data drift, overfitting and more…Jun 4, 20221Jun 4, 20221
Published inIBM Data Science in PracticeRisk-Based Customer Segmentation within BankingIntroductionDec 14, 20213Dec 14, 20213
Published inTDS ArchiveHow to conduct A/B Testing?The idea of A/B testing is to present different content to different variants (user groups), gather their reactions and user behaviour and…Aug 5, 20202Aug 5, 20202
Published inTDS ArchiveCustomer Churn Prediction within Music Streaming using PySparkWhy is customer churn important?Jul 20, 20201Jul 20, 20201
Published inTDS ArchiveTop 8 Books to Study Data Science and Machine Learning in 2020This article covers some of the most popular books on Data Science and is to assist newcomers with exploring the world of data science…Jul 6, 20202Jul 6, 20202
Published inTDS ArchiveWhom Should Starbucks Send Offerings To? — A Predictive Analysis on Customer BehaviourBusiness UnderstandingJun 3, 20202Jun 3, 20202
Classifying twitter disaster response messagesWe are facing a global health crisis due to COVID-19 — one that is killing people, spreading human suffering, and upending people’s lives…Apr 26, 20202Apr 26, 20202
