So What Math: Mathematical optimization

Showing posts with label Mathematical optimization. Show all posts

3.5: Mathematics of Gradient Descent - Intelligence and Learning

3.5: Mathematics of Gradient Descent - Intelligence and Learning begin-post-stats The Coding Train • 43K views end-post...

So What Learning January 22, 2018

16. Complexity: P, NP, NP-completeness, Reductions

16. Complexity: P, NP, NP-completeness, Reductions begin-post-stats MIT OpenCourseWare • 72K views end-post-stats ...

Algorithms Complex systems theory Complexity classes Elementary arithmetic Integers Logic Mathematical optimization Set theory

So What Learning January 22, 2018

16. Complexity: P, NP, NP-completeness, Reductions

16. Complexity: P, NP, NP-completeness, Reductions begin-post-stats MIT OpenCourseWare • 65K views end-post-stats ...

Algorithms Complex systems theory Complexity classes Elementary arithmetic Integers Logic Mathematical optimization Set theory

So What Learning January 22, 2018

Neural Network and Backpropagation Algorithm

Neural Network and Backpropagation Algorithm begin-post-stats Machine Learning- Sudeshna Sarkar • 7K views end-post-sta...

Algorithms Artificial neural networks Boolean algebra Elementary mathematics Exponentials Machine learning Mathematical optimization Physics Theoretical computer science

So What Learning January 22, 2018

The Evolution of Gradient Descent

The Evolution of Gradient Descent begin-post-stats Siraj Raval • 40K views end-post-stats begin-duration 9:19 end...

Abstract algebra Calculus Cybernetics Data Learning Mathematical optimization Mathematical terminology Moment (mathematics) Philosophy of science Physical quantities Subfields of physics

So What Learning January 22, 2018

Neural Networks Demystified [Part 4: Backpropagation]

Neural Networks Demystified [Part 4: Backpropagation] begin-post-stats Welch Labs • 321K views end-post-stats beg...

Artificial neural networks Differentiation rules Mathematical analysis Mathematical logic Mathematical optimization Multiplication Programming languages

So What Learning January 22, 2018

20. Dynamic Programming II: Text Justification, Blackjack

20. Dynamic Programming II: Text Justification, Blackjack begin-post-stats MIT OpenCourseWare • 209K views end-post-sta...

Addition Control flow Directed graphs Language Mathematical optimization Mathematical relations Programming languages Theoretical computer science

So What Learning January 22, 2018

Margot Gerritsen on "Linear Algebra - the incredible beauty of math"

Margot Gerritsen on "Linear Algebra - the incredible beauty of math" begin-post-stats Piero Scaruffi • 100K vi...

Algebra Complex systems theory Graph theory Mathematical optimization Mathematics Physical quantities

So What Learning January 22, 2018

Lecture 13 | Generative Models

Lecture 13 | Generative Models begin-post-stats Stanford University School of Engineering • 54K views end-post-stats ...

Artificial neural networks Data Machine learning Mathematical optimization Probability Psychometrics

So What Learning January 22, 2018

How to Read a Research Paper

How to Read a Research Paper begin-post-stats Siraj Raval • 82K views end-post-stats begin-duration 8:44 end-dura...

Cognitive science Computers Formal sciences Game theory Learning Mathematical optimization Ontology Scientific method

So What Learning January 22, 2018

10.16: Neural Networks: Backpropagation Part 3 - The Nature of Code

10.16: Neural Networks: Backpropagation Part 3 - The Nature of Code begin-post-stats The Coding Train • 10K views end-p...

Analytic geometry Artificial neural networks Estimation theory Functions and mappings Machine learning Mathematical notation Mathematical optimization Matrices Physics

So What Learning January 21, 2018

Backpropagation in 5 Minutes

Backpropagation in 5 Minutes begin-post-stats Siraj Raval • 100K views end-post-stats begin-duration 5:29 end-dur...

Abstract algebra Analytic geometry Artificial neural networks Calculus Elementary mathematics Functions and mappings Mathematical optimization Multivariable calculus

So What Learning January 21, 2018

Lecture 7 | Training Neural Networks II

Lecture 7 | Training Neural Networks II begin-post-stats Stanford University School of Engineering • 54K views end-post...

Computational neuroscience Differential operators Elementary mathematics Mathematical optimization Moment (mathematics) Motion (physics) Physics Statistical inference

So What Learning January 21, 2018

How to Win Slot Machines - Intro to Deep Learning #13

How to Win Slot Machines - Intro to Deep Learning #13 begin-post-stats Siraj Raval • 29K views end-post-stats beg...

Algorithms Artificial intelligence Dimensionless numbers Machine learning Mathematical objects Mathematical optimization Metaphysics Probability distributions

So What Learning January 21, 2018