jgvfwstone/ArtificialIntelligenceEngines
Computer code collated for use with Artificial Intelligence Engines book by JV Stone
This collection of computer code helps you understand the mathematical foundations of deep learning, accompanying the book "Artificial Intelligence Engines". It provides practical examples that demonstrate the concepts discussed in the book, allowing you to see how the theoretical mathematics translate into working code. This resource is for students, researchers, or anyone interested in the underlying math of AI and deep learning.
No commits in the last 6 months.
Use this if you are reading the book "Artificial Intelligence Engines" and want to explore practical code examples that illustrate the mathematical concepts of deep learning.
Not ideal if you are looking for production-ready deep learning code or a comprehensive programming guide for building AI applications.
Stars
65
Forks
16
Language
Python
License
MIT
Category
Last pushed
Nov 28, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/jgvfwstone/ArtificialIntelligenceEngines"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Marktechpost/AI-Tutorial-Codes-Included
Codes/Notebooks for AI Projects
microsoft/AI-For-Beginners
12 Weeks, 24 Lessons, AI for All!
airbus/scikit-decide
AI framework for Reinforcement Learning, Automated Planning and Scheduling
nearai/program_synthesis
Program Synthesis
papagiannakis/Elements
Project Elements: A computational entity-component-system in a scene-graph pythonic framework,...