Practical session on support vector machines and random forest
Day 3, 1:00 - 2:30 pm (tutorial)
Tiwonge Msulira Banda
This practical session will provide students the opportunity to to use the two classification algorithms: Support Vector Machines (SVM) and Random Forest (RF) on real datasets to make classification predictions.
Tiwonge Msulira Banda has over 14 years’ experience in ICT4D project management. He is responsible for projects and administration at UbuntuNet Alliance, the regional research and education network for Eastern and Southern Africa. He is an experienced machine learning developer, data analyst and business intelligence analyst. He has a particular interest in the development and application of data-driven systems that address real life day to day challenges. In his spare time, he likes building data visualization dashboards for whatever data he comes across. He also likes building, training and evaluating machine learning algorithms. He holds an MSc in Information Technology with Business Intelligence; a Masters in Business Administration and a BSc in Environment Science.