Label-Encoding-Ordinal-Encoding-1-1

Label Encoding vs Ordinal Encoding | Categorical Variable Encoding

Machine Learning algorithm cant work on categorical data so we have to encode categorical variables in a numerical format and in this blog we working on Label Encoding and Ordinal Encoding. Below is Jupyter Notebook file to download with practical and prime video tutorial link. What is Ordinal Variables? •Ordinal variables are categorical variables in which the categories can be meaningfully...
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Feature Scaling Standardization and normalization

Feature Scaling – Standardization vs Normalization Explain in Detail

What is Feature Scaling? •Feature Scaling is a method to scale numeric features in the same scale or range (like:-1 to 1,  0 to 1). •This is the last step involved in Data Preprocessing and before ML model training. •It is also called as data normalization. •We apply Feature Scaling on independent variables. •We fit feature scaling with train data and transform on train and test data....
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handling missing values

Best 6 Methods to Handling Missing Values/Data Smartly – Data Cleaning

Data is a powerful weapon to handle the world on the finger. As you know Customer is the king of business but customer's data is the god of the customer and if you have customer's god in your database then you can handle customers according to you. It is the truth. Now let's talk about data cleaning, In this tutorial, we are working on How to handle missing values or data by different methods to...
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