Machine_Learning_Fundamentals

This repository has a collection of guided Jupyter notebooks that cover essential ML concepts.

Notebooks Included

Linear Regression
Data Preprocessing
Data Types and Attributes
Binary Classification
Clustering
K-Nearest Neighbors (KNN)
Naive Bayes
Comprehensive EDA performed on "Data Science Jobs and Salary" dataset
Comprehensive EDA performed on "Loan Approval Prediction" dataset
Models implementation performed on "Loan Approval Prediction" dataset

Features

Comprehensive
Practical Examples
Easy to Understand

Environment

Python
Jupyter Notebook

Usage

Learning: Use the notebooks to deepen your understanding of various ML concepts.
Teaching: Share these notebooks with students to facilitate learning in classrooms or workshops.