Foundational Mathematics
8
Optimization
Applied Machine Learning for Aerospace Systems
Preface
1
Introduction to Machine Learning
Foundational Mathematics
2
Linear Algebra
3
Functions & Function Spaces
4
Random Variables
5
Random Processes and Sequences
6
Bayesian Inference
7
Monte Carlo Methods
8
Optimization
9
Function Approximation
10
Neural Networks
Machine Learning Algorithms
11
Data Pre-Processing
12
Supervised Learning
13
Unsupervised Learning
14
Dimensionality Reduction
Aerospace Applications
15
Aerospace Application 1
16
Aerospace Application 2
17
Summary
References
Table of contents
8.1
Convex Sets
8.2
Convex Functions
8.3
Some Useful Inequalities
8
Optimization
8.1
Convex Sets
8.2
Convex Functions
8.3
Some Useful Inequalities
7
Monte Carlo Methods
9
Function Approximation