Overview: Feature engineering is a power full tool for improving the performance of machine learning models. Basically, it involves inn creating a new input feature or transforming existing ones to help models learn more effectively from the data. In this blog we are going to see how the engineering features are going to be perform …
How to Engineer New Features for Better Model Performance Read More »
Overview: When we start a Machine Learning model, not all the features (columns) carry the same scale for example one feature might be in meters while the other is in kilometer. This creates an imbalance and confuses for the algorithms such as SVM and KNN. So, to handle these features we can use the Feature …
Feature Scaling: Standardization vs Normalization Read More »
Introduction Whenever we perform the real-world Machine Learning projects, Dealing with missing data is the first step. Datasets collected from various sources such as surveys, web scraping, Kaggle…. etc. often contain the missing or incomplete values in the dataset. So, in this blog I am going to perform various technique to handle the missing data. …