📐 ML Fundamentals

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

ML Fundamentals

Five Factorizations of a Matrix

MIT OpenCourseWare Beginner 2y ago

ML Fundamentals

Lecture 5 Part 1: Derivative of Matrix Determinant and Inverse

MIT OpenCourseWare Beginner 2y ago

ML Fundamentals

Lecture 5 Part 2: Forward Automatic Differentiation via Dual Numbers

MIT OpenCourseWare Beginner 2y ago

ML Fundamentals

Lecture 5 Part 3: Differentiation on Computational Graphs

MIT OpenCourseWare Beginner 2y ago

ML Fundamentals

Lecture 1 Part 1: Introduction and Motivation

MIT OpenCourseWare Beginner 2y ago

ML Fundamentals

Lecture 8 Part 1: Derivatives of Eigenproblems

MIT OpenCourseWare Beginner 2y ago

ML Fundamentals

Lecture 3 Part 1: Kronecker Products and Jacobians

MIT OpenCourseWare Beginner 2y ago

ML Fundamentals

Lecture 3 Part 2: Finite-Difference Approximations

MIT OpenCourseWare Beginner 2y ago

ML Fundamentals

Lecture 2 Part 1: Derivatives in Higher Dimensions: Jacobians and Matrix Functions

MIT OpenCourseWare Beginner 2y ago

ML Fundamentals

Lecture 4 Part 2: Nonlinear Root Finding, Optimization, and Adjoint Gradient Methods

MIT OpenCourseWare Beginner 2y ago

ML Fundamentals

Lecture 7 Part 2: Second Derivatives, Bilinear Forms, and Hessian Matrices

MIT OpenCourseWare Beginner 2y ago

ML Fundamentals

Lecture 4 Part 1: Gradients and Inner Products in Other Vector Spaces

MIT OpenCourseWare Beginner 2y ago

ML Fundamentals

Lecture 2 Part 2: Vectorization of Matrix Functions

MIT OpenCourseWare Beginner 2y ago

ML Fundamentals

Lecture 1 Part 2: Derivatives as Linear Operators

MIT OpenCourseWare Beginner 2y ago

ML Fundamentals

Lecture 8 Part 2: Automatic Differentiation on Computational Graphs

MIT OpenCourseWare Beginner 2y ago

ML Fundamentals

Lecture 7 Part 1: Derivatives of Random Functions

MIT OpenCourseWare Beginner 2y ago

ML Fundamentals

Lecture 6 Part 1: Adjoint Differentiation of ODE Solutions

MIT OpenCourseWare Beginner 2y ago

ML Fundamentals

Lecture 6 Part 2: Calculus of Variations and Gradients of Functionals

MIT OpenCourseWare Beginner 2y ago

ML Fundamentals

2-2: Brainstorming

MIT OpenCourseWare Beginner 3y ago

ML Fundamentals

Lecture 14: Basic Hilbert Space Theory

MIT OpenCourseWare Beginner 3y ago

ML Fundamentals

Lecture 14: Resonance and the S-Matrix

MIT OpenCourseWare Beginner 3y ago

ML Fundamentals

Elephant Toothpaste Reaction

MIT OpenCourseWare Intermediate 3y ago

ML Fundamentals

10A. Networks 2: Molecular Computing, Self-assembly, Genetic Algorithms, Neural Networks

MIT OpenCourseWare Intermediate 3y ago

ML Fundamentals

Lecture 19: Differentiation Rules, Rolle's Theorem, and the Mean Value Theorem

MIT OpenCourseWare Intermediate 3y ago

ML Fundamentals

Lecture 16: The Min/Max Theorem and Bolzano's Intermediate Value Theorem

MIT OpenCourseWare Intermediate 3y ago

ML Fundamentals

Lecture 14: Limits of Functions in Terms of Sequences and Continuity

MIT OpenCourseWare Beginner 3y ago

ML Fundamentals

Lecture 22: Fundamental Theorem of Calculus, Integration by Parts, and Change of Variable Formula

MIT OpenCourseWare Intermediate 3y ago

ML Fundamentals

Lecture 6: Photometric Stereo, Noise Gain, Error Amplification, Eigenvalues and Eigenvectors Review

MIT OpenCourseWare Intermediate 3y ago

ML Fundamentals

AI 101 with Brandon Leshchinskiy

MIT OpenCourseWare Beginner 3y ago

ML Fundamentals

The Human Element in Machine Learning w Catherine D’Ignazio, Jacob Andreas & Harini Suresh (S3:E5)

MIT OpenCourseWare Beginner 4y ago

ML Fundamentals

Part 6: Finding the Nullspace: Solving Ax = 0 by Elimination

MIT OpenCourseWare Intermediate 4y ago

ML Fundamentals

1. Introduction and Matrix Multiplication

MIT OpenCourseWare Beginner 4y ago

ML Fundamentals

20. Asynchronous Distributed Algorithms: Shortest-Paths Spanning Trees

MIT OpenCourseWare Beginner 4y ago

ML Fundamentals

24. Robustness to Dataset Shift

MIT OpenCourseWare Beginner 4y ago

ML Fundamentals

L3.4 Feynman Calculus: Higher-Order Diagrams

MIT OpenCourseWare Beginner 4y ago

ML Fundamentals

L3.5 Feynman Calculus: Divergency

MIT OpenCourseWare Beginner 4y ago

ML Fundamentals

L3.2 Feynman Calculus: Fermi's Golden Rule

MIT OpenCourseWare Beginner 4y ago

ML Fundamentals

L3.3 Feynman Calculus: Toy Theory

MIT OpenCourseWare Beginner 4y ago

ML Fundamentals

L3.1 Feynman Calculus: Introduction

MIT OpenCourseWare Beginner 4y ago

ML Fundamentals

Class 1: Intro and Key Technological Trends Affecting Financial Services

MIT OpenCourseWare Beginner 5y ago

ML Fundamentals

Class 3: Artificial Intelligence in Finance

MIT OpenCourseWare Beginner 5y ago

ML Fundamentals

Class 2: Artificial Intelligence, Machine Learning, and Deep Learning

MIT OpenCourseWare Beginner 5y ago

ML Fundamentals

1. What Makes Healthcare Unique?

MIT OpenCourseWare Beginner 5y ago

ML Fundamentals

3. Deep Dive Into Clinical Data

MIT OpenCourseWare Beginner 5y ago

ML Fundamentals

13. Machine Learning for Mammography

MIT OpenCourseWare Beginner 5y ago

ML Fundamentals

21. Automating Clinical Work Flows

MIT OpenCourseWare Beginner 5y ago

ML Fundamentals

19. Disease Progression Modeling and Subtyping, Part 2

MIT OpenCourseWare Beginner 5y ago

ML Fundamentals

14. Causal Inference, Part 1

MIT OpenCourseWare Beginner 5y ago

📚 Coursera Courses Opens on Coursera · Free to audit

← 1 / 3 → View all →

📚 Coursera Course ↗

Self-paced

Formal Languages and Applications

Opens on Coursera ↗

📚 Coursera Course ↗

Self-paced

Securing AI Systems

Opens on Coursera ↗

📚 Coursera Course ↗

Self-paced

Recommender Systems Complete Course Beginner to Advanced

Opens on Coursera ↗

📚 Coursera Course ↗

Self-paced

Optimize Deep Learning Models for Peak AI

Opens on Coursera ↗

📚 Coursera Course ↗

Self-paced

How Entrepreneurs in Emerging Markets can master the Blockchain Technology

Opens on Coursera ↗

📚 Coursera Course ↗

Self-paced

Exam Prep AIF-C01: AWS Certified AI Practitioner

Opens on Coursera ↗

📚 Coursera Course ↗

Self-paced

Using BigQuery Machine Learning for inference

Opens on Coursera ↗

📚 Coursera Course ↗

Self-paced

Survey of Data Science

Opens on Coursera ↗

📚 Coursera Course ↗

Self-paced

Developing Machine Learning Solutions

Opens on Coursera ↗

📚 Coursera Course ↗

Self-paced

Deep Learning RNN & LSTM: Stock Price Prediction

Opens on Coursera ↗

📚 Coursera Course ↗

Self-paced

Machine Learning for Data Analysis

Opens on Coursera ↗

📚 Coursera Course ↗

Self-paced

Generative Deep Learning with TensorFlow

Opens on Coursera ↗

📚 Coursera Course ↗

Self-paced

Introduction to Data, Signal, and Image Analysis with MATLAB

Opens on Coursera ↗

📚 Coursera Course ↗

Self-paced

Building Resilient Streaming Systems on GCP em Português Brasileiro

Opens on Coursera ↗

📚 Coursera Course ↗

Self-paced

Computer Vision in Microsoft Azure

Opens on Coursera ↗

📚 Coursera Course ↗

Self-paced

Regression Analysis for Statistics & Machine Learning in R

Opens on Coursera ↗

📚 Coursera Course ↗

Self-paced

Responsible Innovation and Trustworthy AI

Opens on Coursera ↗

📚 Coursera Course ↗

Self-paced

Databricks Machine Learning Fundamentals

Opens on Coursera ↗