Applying Machine Learning at Work
You've heard a lot about creating business value with intelligent algorithms: it's finally time to roll up our sleeves and make it happen. In this chapter, we are going to experience what it means to apply machine learning to tangible cases by going through a few step-by-step tutorials. Our companion KNIME is back on stage: we will learn how to build workflows for implementing machine learning models using real-world data. We are going to meet a few specific algorithms and learn the intuitive mechanisms behind how they operate. We'll glimpse into their underlying mathematical models, focusing on the basics to comprehend their results and leverage them in our work.
This practical chapter will answer several questions, including:
- How do I make predictions using supervised machine learning algorithms in KNIME?
- How can I check whether a model is performing well?
- How do we avoid the risk of overfitting?
- What techniques...
