Normalization Techniques in Machine Learning: Data Science with Python Guide (2026)

Progress 3 / 10

Introduction to Data Science and Python

Python Programming Fundamentals for Data Science

Setting Up Data Science Environment

NumPy for Scientific and Numerical Computing

Pandas for Data Analysis and Manipulation

Data Cleaning and Data Preprocessing Techniques

Exploratory Data Analysis and Statistics

Data Visualization using Python Libraries

Feature Engineering and Data Transformation

Machine Learning Fundamentals

Supervised Machine Learning Algorithms

Unsupervised Learning and Clustering

Model Evaluation and Optimization

Real World Data Science Projects

Data Science Career Guide and Interview Preparation

Normalization Techniques in Machine Learning

Intermediate Topic 3 of 10

Normalization

Normalization rescales values into a specific range, usually between 0 and 1.

python from sklearn.preprocessing import MinMaxScaler scaler = MinMaxScaler() scaled_data = scaler.fit_transform([[10],[20],[30]])

Next Tutorial: Standardization Techniques