Machine Learning Essentials Repository

Welcome to the Machine Learning Essentials repository! This repository contains foundational tools and libraries commonly used in machine learning projects. Whether you're working on data manipulation, model building, or data visualization, this repo provides key resources for your journey.

Contents

This repository covers various essential topics and code examples for the following:

Data Manipulation with Pandas:

• Loading and exploring datasets
• Cleaning and preprocessing data
• Handling missing values
• Data transformation and aggregation
• Numerical Computations with NumPy:

Data Visualization with Matplotlib:

• Creating insightful charts and graphs
• Customizing plots for analysis
• Plotting distributions, trends, and relationships

Machine Learning with Scikit-learn:

• Building basic machine learning models
• Training and evaluating classifiers and regressors
• Cross-validation and hyperparameter tuning
• Model evaluation metrics

Prerequisites

Before running the code, make sure to have the following installed:

Python 3.x Pandas NumPy Matplotlib Scikit-learn