Machine Learning Workshop

Machine Learning Workshop

Machine learning is introduced as the science of programming machines to perform human tasks without being explicitly programmed. Email spam recognition, spelling checkers, and platform video recommenders are highlighted as commonly encountered machine learning applications that we explore in our everyday lives. 

In this workshop, two learning objectives were targeted. First, acquiring practical implementation skills for machine learning algorithms using Python. Second, understanding the key criteria for selecting an appropriate machine learning algorithm given a particular case study.

To address the first objective, a comprehensive review of algorithms covering major machine learning models was provided. Afterwards, dedicated labs were conducted using Python. Simple Linear Regression, Multiple Linear Regression, and Logistic Regression were proposed for regression models. For classification models, we covered Decision Trees, Random Forests, and Naïve Bayes. For clustering models, we explored K-means, Nearest Neighbors (NN), and Support Vector Machines (SVM).

To fulfill the second objective, we introduced popular use cases of machine learning and reviewed common machine learning interview questions to assess practical market expectations. 

Workshop Date: 13–14 March 2023
Venue: Online Event