This workshop will provide an overview of modern machine learning methods for predictive analytics and provide hands-on experience with the most important modeling tools. Participants will be introduced to supervised learning for classification and regression, then walk-through a step-by-step tutorial of a typical machine learning application. Participants will apply decision trees, neural networks, and Gaussian processes to real data, using the python programming language and scikit-learn library in interactive Jupyter notebooks.
Who should attend?
- Managers responsible for data related activities or functions that rely on data analysis
- Professionals who work with data analysts or who do data analysis on their own
- Data analysts wishing to broaden their understanding of applied data analytics