Practice-Notebook

This id s detailed notebook with most of the techniques used in Machine learning

What we have covered:

Beginner Friendly Detailed Explained EDAs – For anyone at the beginnings of DS/ML journey ✔️

BIAS & VARIANCE TRADEOFF ✔️

LINEAR ALGORITHMS ✔️

NONLINEAR ALGORITHMS ✔️

The Most Used Methods to Deal with MISSING VALUES ✔️

Beginner Friendly End to End ML Project- Classification with Imbalanced Data ✔️

How to Prevent the Data Leakage ? ✔️

The Most Common EVALUATION METRICS- A Gentle Intro ✔️

Feature Selection-The Most Common Methods to Know ✔️