10 Best Python Code Snippets for Everyday Machine Learning in 2025

These 10 Python snippets will help you in both automation and slash your coding time in half!

Image Credits: Zach Graves

Ever wondered how devs in big MNCs and Startups always seem to have the perfect Python code ready for any ML task?😏
It’s like they’ve unlocked a secret cheat code 🕹️ that makes even the most complex ML tasks look like a walk in the park 🌳.

Well, guess what? It’s not magic — just knowing the right snippets! 💡
In 2025, machine learning is evolving faster than ever 🚀, and staying ahead means you gotta have these game-changing Python hacks 🔥.

Ready to level up and slash your coding time in half? ⏱️
These 10 Python snippets will have you coding like a machine in no time! 🖥️

Data Preprocessing Snippets🤩:

Handling missing values (With explanation) 🧐

import pandas as pd
from sklearn.impute import SimpleImputer

# Sample Values
data = {'Age': [25, 27, None, 22, 300], 'Salary': [50000, 60000, 55000, None, 100000], 'Color': ['Red', 'Green', None, 'Blue', 'Red']}
df = pd.DataFrame(data)

#   1. Mean Imputation (for numerical data with normal distribution)
print("Mean Imputation:")…