walternyamutamba-svg/IndabaX-Botswana

# Deep Learning IndabaX Botswana ## Applied Machine Learning for Real-World Business Problems **Author:** Walter M Nyamutamba **Event:** Deep Learning IndabaX Botswana **Project Type:** Applied Data Science & Machine Learning Tutorial **Notebook:** `IndabaX_Botswana_DataScience_Industry.ipynb` --- # Project Overview This project was developed as part of an applied data science tutorial for IndabaX Botswana. The notebook demonstrates how machine learning can be used to solve practical industry problems through predictive analytics and business-focused decision-making. The tutorial is designed to simulate a real-world data science workflow used in industry, moving beyond theory into operational business applications. The central business problem explored in the notebook is: > *How can organisations use customer and operational data to make smarter, data-driven decisions?* The project demonstrates the complete machine learning lifecycle, including: - Data loading and preprocessing - Exploratory Data Analysis (EDA) - Feature engineering - Predictive modelling - Model evaluation - Business interpretation of results - Strategic recommendations --- # Repository Structure ```text . ├── README.md ├── IndabaX_Botswana_DataScience_Industry.ipynb ├── IndabaX_Botswana_EDA_Python.pptx └── Student_Practice_Files_IndabaX_Botswana/ ├── Project1_Insurance_Telemarketing.ipynb ├── Project2_Telecom_Churn.ipynb ├── Project3_CreditCard_Upgrade.ipynb ├── Project4_Microfinance_Repayment.ipynb ├── Project5_Health_Insurance_Enrolment.ipynb │ ├── insurance_telemarketing.csv ├── telecom_churn_campaign.csv ├── creditcard_upsell_campaign.csv ├── microfinance_repayment.csv └── health_insurance_enrolment.csv ``` --- # Main Learning Objectives This project focuses on teaching practical machine learning skills that are directly transferable to industry environments. Key objectives include: - Understanding structured business datasets - Performing exploratory data analysis - Building …