[100 Days of ML Code] OneHotEncoder
One Hot Encoding is process by which categorical variables are converted  into a form that could be provided to ML algorithms to do a better job  in prediction.   Normally, we will have a dataset of:  ╔════════════╦════════╗  ║ CompanyName║ Price  ║ ╠════════════╣════════║  ║ VW         ║ 20000  ║ ║ Acura      ║ 10011  ║ ║ Honda      ║ 50000  ║ ║ Honda      ║ 10000  ║ ╚════════════╩════════╝    Many ML algorithms cannot work with label data (as a string) directly. Therefore, we need to convert these labels into some numeric value:    ╔════════════╦═════════════════╦════════╗  ║ CompanyName Categoricalvalue ║ Price  ║ ╠════════════╬═════════════════╣════════║  ║ VW         ╬      1          ║ 20000  ║ ║ Acura      ╬      2          ║ 10011  ║ ║ Honda      ╬      3          ║ 50000  ║ ║ Honda      ╬      3          ║ 10000  ║ ╚════════════╩═════════════════╩════════╝   Now, 'categoricalValue' is a numerical value that represents the companyName.   However, the problem with the ab...