Let's Apply Science to Data

Improve the Accuracy Of Model by 22.5% Introduction :     In a Machine Learning model, Accuracy is the key to decide whether the model is precise to use or not. We  all thrive for a better  model which gives higher accuracy. Accuracy of a model depends on various criteria such as Feature Selection, Handling of Null or Missing values in data set, Hyper Parameters of Algorithms, Feature Scaling and so on. This may seem a bit complicated but when we actually dive into it, we will get to know how easy it would be to improve the performance of our Machine learning Model. So let's get started. We are going to use Red wine - Quality data set which contains 11 features and a Target column. Techniques to Improve Accuracy :  Selecting appropriate Features  Handling of Null or Missing Values  Hyper Parameter Tuning  Feature Scaling.