Are you aware of these Must-Know Plots in Data Science?
Plots that every Data Science Professional should know
In the field of data science, visualizations play a pivotal role in understanding complex datasets, identifying patterns, and communicating findings effectively. From classic statistical distributions like the normal distribution to sophisticated machine learning techniques such as logistic regression plots and ROC curves, each visualization offers a unique perspective on the data.
In this blog, we will explore some of the most essential and powerful visualizations used by data scientists to gain insights from data.
1. Bias-Variance Tradeoff
What is Bias?
The bias is the difference between the average prediction of our model and the actual value that we are trying to predict. High bias means the predictions are inaccurate and far away from the actual/expected value. A model with high bias underfits the data.
Bias is the error or inaccuracy of the machine learning model’s predictions. High bias means high error.
What is Variance?
