Machine Learning Demos

This repository contains a collection of different machine learning project demos. Each demo showcases a specific aspect of machine learning, ranging from data preprocessing to advanced model training and evaluation. The goal of this repository is to provide easy-to-follow examples that can help users understand and apply machine learning techniques to real-world problems.

• Data Preprocessing: Techniques and tools for cleaning and preparing data for machine learning.
• Model Training: Examples of training various machine learning models.
• Model Evaluation: Methods to evaluate and interpret model performance.
• Visualization: Tools for visualizing data and model results.
• Deployment: Steps to deploy machine learning models to production.

• Python 3.11.4
• Git

1. Clone the repository:

   git clone https://github.com/EdFlo15/notebooks.git
   cd notebooks

2. Usage:

   For each project you want to execute, enter the project directory, create a virtual environment, and install the necessary libraries

3. Set up a virtual environment:

   python -m venv venv

4. Activate the virtual environment:

   • On Windows:

     .\venv\Scripts\activate

   • On macOS and Linux:

     source venv/bin/activate

5. Install dependencies:

   pip install -r requirements.txt