How to Visualize Bias and Variance
Machine learning models represent the learning output from a machine in such a way that, it can be used in the future to predict or understand similar kinds of data by which the model had been trained. We will be using NumPy for data generation and calculations. Matplotlib and Seaborn are useful for visualizing the generated data points and predicted data points. We use Scikit-learn for model building and Pandas for handling the data. Our objective is to see what is happening in terms of bias and variance.