Introduction to Model Evaluation

In the ever-evolving landscape of data science and ML, the development of predictive models has become a fundamental component of decision-making across various domains. These models, ranging from simple linear regressions to complex deep neural networks, hold the promise of uncovering valuable insights and making accurate predictions. However, building a model is just the first step in the process. The true test of a model’s worth lies in its ability to perform in the real world.

Model evaluation is the critical practice of assessing the performance and generalization capabilities of ML ...