Battle of the Ensemble -- Random Forest vs Gradient Boosting

If you have spent some time in the world of machine learning, you would have undoubtedly heard of a concept called the bias-variance tradeoff. It is one of the most important concepts any machine learning practitioner should learn and be aware of. Essentially, the bias-variance tradeoff is a conundrum in machine learning which states that models with low bias will usually have high variance and vice versa. Bias is the difference between the actual value and the expected value predicted by the model. A model with a high bias is said to be oversimplified as a result, underfitting the data.