Practical implementation of selected algorithms, concepts and techniques from data science, data analysis, data characterization and data visualization topics.
Feature scaling is a method used to normalize the range of independent variables or features of a dataset. In data processing, it is also known as data normalization and is generally performed during the data preprocessing step. Implementation of two of the feature scaling methods, mean normalization and standardization of a dataset can be understood here.
Please note that the code and technical details made available are for anyone interested to learn. The repo is not open for collaboration.
If you happen to use the code from this repo, please cite my user name along with link to my profile: https://github.com/balarcode. Thank you!