The workshop will center on classical Machine Learning, examining both its historical and present states and comparing it to Deep Learning to identify use cases where it excels. Participants will learn how to optimise their classical ML algorithm performance using popular classical Machine Learning libraries like Scikit-learn, Pandas, and Xgboost.

The first part will focus on:

• A short history of AI
• Current status of Machine Learning and Deep Learning
• Classical Machine Learning typical use cases
• Overview of Hardware and Software by Intel

The second part will focus on Intel optimisation of classical Machine Learning libraries:

• Intel Distribution of Python
• Intel Distribution of Modin
• Intel optimisations for Xgboost
• Intel Extension for scikit-learn

Prerequisites:

• Basic knowledge of Python
• AI Training Series: Orientation Session (or comparable previous knowledge)