Expand description
If this is your first time using Easy ML you should check out some of the examples to get an overview of how to use matrices or tensors then check out the Matrix type or Tensor type for what you need.
Matrix
is a straightforward 2 dimensional matrix with APIs built around the notion of
rows and columns; Tensor
is a named tensor with full API support for 0 to 6 dimensions.
Naturally, a 2 dimensional tensor is also a matrix, but the APIs are more general so may
be less familiar or ergonomic if all you need is 2 dimensional data.
Examples
API Modules
- Matrices
- Named tensors
- Linear Algebra
- Distributions
- (Automatic) Differentiation
- Numerical type definitions
Miscellaneous
Modules
(Automatic) Differentiation helpers
Models of distributions that samples can be drawn from.
K-means example
Linear algebra algorithms on numbers and matrices
Linear regression examples
Logistic regression example
Generic matrix type.
Naïve Bayes examples
Neural Network training examples
Numerical type definitions.
SARSA and Q-learning using a Matrix for a grid world.
Generic N dimensional named tensors.
Using custom numeric types examples.
Web Assembly examples