Hello user:- Welcome to QuickNKode.
In this program we can quickly encode a set of required columns with categorical values in our dataset so that we can use that dataset for transformation or training a model. This program supports the types encoding methods namely One Hot Encoding and Label Encoding. The program is extremely flexible and efficiently encodes any huge dataset. This program is also flexible to handle users mistakes.
Currently I am planning to turn this program into a small application for PC users and I am also planning to connect this program to the main program for which it was original plaaned for. This program is a sibling from the QuickSeries family I have been working on for some time. In this series of programs the main and the final program is named QuickLEarn or QML which has not been uploaded till now. That program will predict and find the best model needed for a particular set of data to solve a particular problem.
The order of progress of the programs in this series is as follows:-
- QuickWash - A program to quickly work on missing values.
- QuickForm - A program to quickly transform a dataset.
- QuickNKode - A program to quickly encode a dataset.
- QuickLearn / QML - A program to quickly learn the best model for a dataset.
Future plans:-
- I am also working on making these programs to work completely automatically which will be named AutoFiller, AutoFormer, AutoNKoder, AutoModel.
- I am learning python packages to make computer applications for this programs so that any normal user can use them.
System Requirements:-
- RAM and CPU: Generic.
- Python version 3.7 programming language IDE
- Python packages: Pandas and ScikitLearn
It does not require much powerful cpu or ram to run this since it is only a small program. But, to run this you will need the Python IDE installed along with Pandas package and ScikitLearn.
You can run this program directly if you have installed Python along with the packages or you can run it as a Python program also.