✕ Clear filters
8,992 lessons

📐 ML Fundamentals

Neural networks, backpropagation, gradient descent — the maths behind AI

All ▶ YouTube 118,111📚 Coursera 18,103🏛 Archive.org 1🎤 TED 1
Rubber used to be useless…
📐 ML Fundamentals
Rubber used to be useless…
Veritasium Intermediate 1mo ago
This is why you NEED technical debt
📐 ML Fundamentals
This is why you NEED technical debt
DeepLearningAI Beginner 1mo ago
Migrate from Foreign Parquet to Managed Delta in 3 simple steps
📐 ML Fundamentals
Migrate from Foreign Parquet to Managed Delta in 3 simple steps
Databricks Beginner 1mo ago
Lec 05. Architectures: Graphs
📐 ML Fundamentals
Lec 05. Architectures: Graphs
MIT OpenCourseWare Beginner 1mo ago
Lec 09. Hacker's Guide to Deep Learning
📐 ML Fundamentals
Lec 09. Hacker's Guide to Deep Learning
MIT OpenCourseWare Beginner 1mo ago
Lec 16. Generative Models: Conditional Models
📐 ML Fundamentals
Lec 16. Generative Models: Conditional Models
MIT OpenCourseWare Beginner 1mo ago
Lec 15. Generative Models: Representation Learning Meets Generative Modeling
📐 ML Fundamentals
Lec 15. Generative Models: Representation Learning Meets Generative Modeling
MIT OpenCourseWare Beginner 1mo ago
Lec 04. Architectures: Grids
📐 ML Fundamentals
Lec 04. Architectures: Grids
MIT OpenCourseWare Beginner 1mo ago
Lec 02. How to Train a Neural Net
📐 ML Fundamentals
Lec 02. How to Train a Neural Net
MIT OpenCourseWare Beginner 1mo ago
Lec 17. Generalization: Out-of-Distribution (OOD)
📐 ML Fundamentals
Lec 17. Generalization: Out-of-Distribution (OOD)
MIT OpenCourseWare Beginner 1mo ago
Lec 01. Introduction to Deep Learning
📐 ML Fundamentals
Lec 01. Introduction to Deep Learning
MIT OpenCourseWare Beginner 1mo ago
Lec 20. Scaling Laws
📐 ML Fundamentals
Lec 20. Scaling Laws
MIT OpenCourseWare Beginner 1mo ago
Lec 13. Representation Learning: Theory
📐 ML Fundamentals
Lec 13. Representation Learning: Theory
MIT OpenCourseWare Beginner 1mo ago
Lec 10. Architectures: Memory
📐 ML Fundamentals
Lec 10. Architectures: Memory
MIT OpenCourseWare Beginner 1mo ago
Lec 11. Representation Learning: Reconstruction-Based
📐 ML Fundamentals
Lec 11. Representation Learning: Reconstruction-Based
MIT OpenCourseWare Beginner 1mo ago
Lec 14. Generative Models: Basics
📐 ML Fundamentals
Lec 14. Generative Models: Basics
MIT OpenCourseWare Beginner 1mo ago
Lec 03. Approximation Theory
📐 ML Fundamentals
Lec 03. Approximation Theory
MIT OpenCourseWare Beginner 1mo ago
Lec 12. Representation Learning: Similarity-Based
📐 ML Fundamentals
Lec 12. Representation Learning: Similarity-Based
MIT OpenCourseWare Beginner 1mo ago
Lec 23. Metrized Deep Learning
📐 ML Fundamentals
Lec 23. Metrized Deep Learning
MIT OpenCourseWare Advanced 1mo ago
Lec 07. Scaling Rules for Optimization
📐 ML Fundamentals
Lec 07. Scaling Rules for Optimization
MIT OpenCourseWare Beginner 1mo ago
Lec 06. Generalization Theory
📐 ML Fundamentals
Lec 06. Generalization Theory
MIT OpenCourseWare Beginner 1mo ago
PyTorch Tutorial
📐 ML Fundamentals
PyTorch Tutorial
MIT OpenCourseWare Beginner 1mo ago
Lec 18. Transfer Learning: Models
📐 ML Fundamentals
Lec 18. Transfer Learning: Models
MIT OpenCourseWare Beginner 1mo ago
Using Bots to Find Bugs in Games with Snowcap
📐 ML Fundamentals
Using Bots to Find Bugs in Games with Snowcap
AI and Games Beginner 1mo ago