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📐 ML Fundamentals

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

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Lec 09. Hacker's Guide to Deep Learning
ML Fundamentals ⚡ AI Lesson
Lec 09. Hacker's Guide to Deep Learning
MIT OpenCourseWare Beginner 7mo ago
Lec 08. Architectures: Transformers
Large Language Models ⚡ AI Lesson
Lec 08. Architectures: Transformers
MIT OpenCourseWare Beginner 7mo ago
Lec 11. Representation Learning: Reconstruction-Based
Deep Learning ⚡ AI Lesson
Lec 11. Representation Learning: Reconstruction-Based
MIT OpenCourseWare Beginner 7mo ago
2: Training Deep NNs (cont.); Introduction to Keras/Tensorflow; Application to Tabular Data
Deep Learning ⚡ AI Lesson
2: Training Deep NNs (cont.); Introduction to Keras/Tensorflow; Application to Tabular Data
MIT OpenCourseWare Beginner 8mo ago
Lec 15. Generative Models: Representation Learning Meets Generative Modeling
Deep Learning ⚡ AI Lesson
Lec 15. Generative Models: Representation Learning Meets Generative Modeling
MIT OpenCourseWare Beginner 7mo ago
Lec 12. Representation Learning: Similarity-Based
Deep Learning ⚡ AI Lesson
Lec 12. Representation Learning: Similarity-Based
MIT OpenCourseWare Beginner 7mo ago
Lec 16. Generative Models: Conditional Models
Deep Learning ⚡ AI Lesson
Lec 16. Generative Models: Conditional Models
MIT OpenCourseWare Beginner 7mo ago
Lec 04. Architectures: Grids
Deep Learning ⚡ AI Lesson
Lec 04. Architectures: Grids
MIT OpenCourseWare Beginner 7mo ago
Lecture 9: Chernoff Bounds
Mathematical Foundations ⚡ AI Lesson
Lecture 9: Chernoff Bounds
MIT OpenCourseWare Beginner 9mo ago
Lecture 12: Time Series Analysis
Data Analytics & Business Intelligence ⚡ AI Lesson
Lecture 12: Time Series Analysis
MIT OpenCourseWare Beginner 9mo ago
Lecture 1: Fluid Dynamics
ML Fundamentals ⚡ AI Lesson
Lecture 1: Fluid Dynamics
MIT OpenCourseWare Beginner 4mo ago
Session 10: Non-conservative Processes in Estuaries/ Groundwater/Hydrothermal
ML Fundamentals ⚡ AI Lesson
Session 10: Non-conservative Processes in Estuaries/ Groundwater/Hydrothermal
MIT OpenCourseWare Intermediate 6mo ago
Lec 23. Metrized Deep Learning
ML Fundamentals ⚡ AI Lesson
Lec 23. Metrized Deep Learning
MIT OpenCourseWare Advanced 7mo ago
Lecture 06: Projections and Smoothing
RAG & Vector Search ⚡ AI Lesson
Lecture 06: Projections and Smoothing
MIT OpenCourseWare Intermediate 10mo ago
Lec 14. Generative Models: Basics
Deep Learning ⚡ AI Lesson
Lec 14. Generative Models: Basics
MIT OpenCourseWare Beginner 7mo ago
1: Introduction to Neural Networks and Deep Learning; Training Deep NNs
ML Fundamentals ⚡ AI Lesson
1: Introduction to Neural Networks and Deep Learning; Training Deep NNs
MIT OpenCourseWare Beginner 8mo ago
Video 12b: Chorales as a Corpus
Algorithms & Data Structures ⚡ AI Lesson
Video 12b: Chorales as a Corpus
MIT OpenCourseWare Advanced 11mo ago
Lec 03. Approximation Theory
ML Fundamentals ⚡ AI Lesson
Lec 03. Approximation Theory
MIT OpenCourseWare Beginner 7mo ago
Lecture 23: Introduction to Machine Learning
ML Fundamentals ⚡ AI Lesson
Lecture 23: Introduction to Machine Learning
MIT OpenCourseWare Beginner 9mo ago
Video 3a: Introduction to Pitch Representation
RAG & Vector Search ⚡ AI Lesson
Video 3a: Introduction to Pitch Representation
MIT OpenCourseWare Beginner 11mo ago
Lec 17. Generalization: Out-of-Distribution (OOD)
ML Fundamentals ⚡ AI Lesson
Lec 17. Generalization: Out-of-Distribution (OOD)
MIT OpenCourseWare Beginner 7mo ago
7: Deep Learning for Natural Language – Transformers
Large Language Models ⚡ AI Lesson
7: Deep Learning for Natural Language – Transformers
MIT OpenCourseWare Beginner 8mo ago
Lecture 8: Regression Analysis (cont.)
Mathematical Foundations ⚡ AI Lesson
Lecture 8: Regression Analysis (cont.)
MIT OpenCourseWare Intermediate 9mo ago
Lec 02. How to Train a Neural Net
ML Fundamentals ⚡ AI Lesson
Lec 02. How to Train a Neural Net
MIT OpenCourseWare Beginner 7mo ago
Lec 01. Introduction to Deep Learning
ML Fundamentals ⚡ AI Lesson
Lec 01. Introduction to Deep Learning
MIT OpenCourseWare Beginner 7mo ago
Lec 07. Scaling Rules for Optimization
ML Fundamentals ⚡ AI Lesson
Lec 07. Scaling Rules for Optimization
MIT OpenCourseWare Beginner 7mo ago
Lec 06. Generalization Theory
ML Fundamentals ⚡ AI Lesson
Lec 06. Generalization Theory
MIT OpenCourseWare Beginner 7mo ago
Lecture 20: Homogeneous Dynamics, Part 1
RAG & Vector Search ⚡ AI Lesson
Lecture 20: Homogeneous Dynamics, Part 1
MIT OpenCourseWare Beginner 10mo ago
Class 28 Video: Feature Extraction and Machine Learning (II)
ML Fundamentals ⚡ AI Lesson
Class 28 Video: Feature Extraction and Machine Learning (II)
MIT OpenCourseWare Advanced 11mo ago
Lecture 5: Nash Equilibrium
AI Agents & Automation ⚡ AI Lesson
Lecture 5: Nash Equilibrium
MIT OpenCourseWare Intermediate 4mo ago
Lec 05. Architectures: Graphs
ML Fundamentals ⚡ AI Lesson
Lec 05. Architectures: Graphs
MIT OpenCourseWare Beginner 7mo ago
Lec 24. Inference Methods for Deep Learning
Deep Learning ⚡ AI Lesson
Lec 24. Inference Methods for Deep Learning
MIT OpenCourseWare Intermediate 7mo ago
Lec 20. Scaling Laws
ML Fundamentals ⚡ AI Lesson
Lec 20. Scaling Laws
MIT OpenCourseWare Beginner 7mo ago
Lec 13. Representation Learning: Theory
ML Fundamentals ⚡ AI Lesson
Lec 13. Representation Learning: Theory
MIT OpenCourseWare Beginner 7mo ago
Lecture 2: Mechanics of Sediment Transport
ML Fundamentals ⚡ AI Lesson
Lecture 2: Mechanics of Sediment Transport
MIT OpenCourseWare Beginner 4mo ago
Lecture 25: Common Knowledge
AI Agents & Automation ⚡ AI Lesson
Lecture 25: Common Knowledge
MIT OpenCourseWare Beginner 4mo ago
5: Deep Learning for Natural Language – The Basics
ML Fundamentals ⚡ AI Lesson
5: Deep Learning for Natural Language – The Basics
MIT OpenCourseWare Beginner 8mo ago
Class 8 Video: Hierarchies (II): Streams and Recursions
ML Fundamentals ⚡ AI Lesson
Class 8 Video: Hierarchies (II): Streams and Recursions
MIT OpenCourseWare Advanced 11mo ago
Video 29a: Feature Extraction and Machine Learning (III): Artificial Intelligence
ML Fundamentals ⚡ AI Lesson
Video 29a: Feature Extraction and Machine Learning (III): Artificial Intelligence
MIT OpenCourseWare Beginner 11mo ago
Lecture 4: Sedimentary Structures Produced by Sediment Transport
ML Fundamentals ⚡ AI Lesson
Lecture 4: Sedimentary Structures Produced by Sediment Transport
MIT OpenCourseWare Beginner 4mo ago
20: Attention
Large Language Models ⚡ AI Lesson
20: Attention
MIT OpenCourseWare Intermediate 5mo ago
Lecture 1, Part I: Introduction of the Class
ML Fundamentals ⚡ AI Lesson
Lecture 1, Part I: Introduction of the Class
MIT OpenCourseWare Beginner 9mo ago
Lecture 24: Sharp Projection Theorems, Part 3: Combining Different Scales
RAG & Vector Search ⚡ AI Lesson
Lecture 24: Sharp Projection Theorems, Part 3: Combining Different Scales
MIT OpenCourseWare Intermediate 10mo ago
Video 7a: Unlocking Duration and Note Objects in music21
AI Tools & Apps ⚡ AI Lesson
Video 7a: Unlocking Duration and Note Objects in music21
MIT OpenCourseWare Beginner 11mo ago
Video 1a: music21 Coding Tutorial for OCW Learners
AI Tools & Apps ⚡ AI Lesson
Video 1a: music21 Coding Tutorial for OCW Learners
MIT OpenCourseWare Beginner 11mo ago
The Ethics of a Free Market
AI Safety & Ethics ⚡ AI Lesson
The Ethics of a Free Market
MIT OpenCourseWare Beginner 4mo ago
Session 14: Primary Production (2)
ML Fundamentals ⚡ AI Lesson
Session 14: Primary Production (2)
MIT OpenCourseWare Intermediate 6mo ago
Lecture 11: Contagious Structure in Projection Theory
AI Safety & Ethics ⚡ AI Lesson
Lecture 11: Contagious Structure in Projection Theory
MIT OpenCourseWare Intermediate 10mo ago