matthewhaynesonline/ai-for-web-devs

This project provides code to accompany the "AI and ML for Web Devs" video series, focusing on teaching AI and ML concepts through hands-on projects tailored for web developers.

37

stars

74

commits

Python

primary language

Oct 12, 2025

updated

machine-learning
tutorial
webdevelopment

README

AI and ML for Web Devs

This is the code that accompanies the AI and ML for Web Devs video series.

Goals

  1. Teach AI and ML Concepts by Building

    • We'll focus on generative AI and machine learning.
    • While many frameworks and libraries already offer the functionalities we'll build, our goal is to understand the underlying mechanics and ideas through hands-on projects.
  2. Provide Practical Implementations

    • The code here is intended to be functional and educational but not necessarily production-ready or reference implementations.

Target Audience

  1. Web Developers
    • This guide is tailored for web developers who want to learn AI and ML in a practical, hands-on way.
    • While we will cover essential theories and concepts, the focus is on practical application rather than academic or research-level depth.

Contributors

matthewhaynesonline/ai-for-web-devs

This project provides code to accompany the "AI and ML for Web Devs" video series, focusing on teaching AI and ML concepts through hands-on projects tailored for web developers.

37

stars

74

commits

Python

primary language

Oct 12, 2025

updated

machine-learning
tutorial
webdevelopment

README

AI and ML for Web Devs

This is the code that accompanies the AI and ML for Web Devs video series.

Goals

  1. Teach AI and ML Concepts by Building

    • We'll focus on generative AI and machine learning.
    • While many frameworks and libraries already offer the functionalities we'll build, our goal is to understand the underlying mechanics and ideas through hands-on projects.
  2. Provide Practical Implementations

    • The code here is intended to be functional and educational but not necessarily production-ready or reference implementations.

Target Audience

  1. Web Developers
    • This guide is tailored for web developers who want to learn AI and ML in a practical, hands-on way.
    • While we will cover essential theories and concepts, the focus is on practical application rather than academic or research-level depth.

Contributors

Languages

Python

52.5%

Svelte

19.9%

Rust

8.6%

TypeScript

5.6%

Jupyter Notebook

4.7%

HTML

3.4%

Jinja

2.8%

Shell

1.2%