Scaling and Descaling Data in Data Science Problems

Note: This same article appears in my account as well In data science problems it is often required to scale data so that the algorithms fit well with the learning goals. How to scale efficiently? There are ways in which we can scale data manually or using some libraries. In this article, I provideContinue reading “Scaling and Descaling Data in Data Science Problems”

Decision Tree using Python With Random Data

Import all required libraries — — — — — — — — — — — — — import pandas as pd from sklearn.model_selection import train_test_split from sklearn.tree import DecisionTreeClassifier from sklearn import tree import matplotlib.pyplot as plt import random import os — — — — — — — — — — — — — —Continue reading “Decision Tree using Python With Random Data”