🚀 An in-depth guide covering the essential topics of AI, Machine Learning (ML), and Deep Learning (DL).
Designed for beginners and advanced learners alike, this book bridges the gap between theory, code, and real-world AI applications.
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This GitHub repository serves as a companion resource to the book, featuring:
✔ 📜 Well-structured Code Examples – Python & C# implementations, directly from the book.
✔ 📊 Interactive Graphs & Visuals – Ready-to-use figures, charts, and plots to reinforce key concepts.
✔ 💡 CodePen & GitHub Integration – Run ML models directly in your browser, no installation needed!
✔ 🎮 (Future) Learning Through a Game – A first-person ML puzzle game in development!
🔹 Want to start learning? Explore the 📂 Code Folder and run your first ML models!
🔹 1. Foundations of AI & Machine Learning
🔹 2. Essential Math for ML (Linear Algebra, Probability, Statistics)
🔹 3. Supervised Learning: Regression & Classification
🔹 4. Support Vector Machines (SVM) & Decision Trees
🔹 5. Unsupervised Learning & Clustering
🔹 6. Neural Networks & Deep Learning (Coming Soon!)
🔹 7. Hands-on ML Projects & AI Challenges
👉 See the full content breakdown in the book!
1️⃣ Clone this repository:
git clone https://github.com/Python840/Machine-Learning-From-Math-to-Models.git