Basic machine learning algorithms and their application

Day 2, 10:30-12:00 am (lecture)

Akuzike Banda

In today’s world, there has been rapid growth in recent years in the area of Machine Learning. Machine learning focuses on building systems with the ability to learn and enhance from experience without being programmed to do so. Algorithms are used to make all of this happen. Machine learning algorithms may fall under: supervised, unsupervised, semisupervised or reinforcement learning. These algorithms are applied in so various ways in everyday life. Applications of these algorithms range from self-driving cars, fraud detection and prevention, automated recommendations on social media and websites, personalized/ customized adverts, face detection and image recognition, DNA sequence analysis, personalized cancer treatments, to virtual personal assistants.

Artificial Neural Networks (ANN) are one popular Machine Learning algorithm. An ANN models the brain in that it consists of simple and highly interconnected processors (neurons) connected by weighted links passing signals. Each neuron receives a number of input signals through its connections. This exercise will involve using an ANN to perform binary classification on Breast Cancer dataset to diagnose whether a tumor is malignant or benign.

Speaker biography

Akuzike Banda is an Assistant Lecturer in Computer Science at the University of Malawi. Her area of expertise is Machine Learning and Artificial Intelligence. Currently she is finalizing a Master of Science in Bioinformatics with Kamuzu University for Health Sciences (KUHES). Her research study titled “Role of Evolutionary Mechanisms on the Emergence of Novel Rotavirus Strains” has a component where she will focus on using Machine Learning to develop a model to predict emergence of novel Rotavirus lineages. As part of her Master’s research work, she has been working with the Virology team at Malawi-Liverpool-Wellcome Trust Clinical Research Programme in Blantyre since 2019. Akuzike has also worked on several information system projects under the Computer Science Department including: Development of the National Agricultural Management Information System (NAMIS) (for the ministry of Agriculture and Food Security), MHealth4Afrika Project (an EU-funded Project, implemented as a Consortium comprising seven countries – Ireland, Norway, Turkey (in the north) and Ethiopia, Kenya, Malawi and South Africa (in the south); and the Malawi Health Management Information System (HMIS) Web Portal among others. Akuzike has some international experience through the Norwegian Partnership Programme for Global Academic Cooperation (NORPART) Master’s exchange student programme which she took part in 2019. Through this programme, she was attached to University of Oslo in Norway for a semester where she successfully completed an Applied Data Analysis and Machine learning course.