Gradient Descent
December 1, 2020
An optimization algorithm for finding the local minimum of a differentiable function. (The red arrows show the … ...
An optimization algorithm for finding the local minimum of a differentiable function. (The red arrows show the … ...
A function which maps values \(x\) to an output value \(y\). Historically, in ML, hypothesis functions are denoted …
Artificial Neural Network (ANN) Layers All learning occurs in the layers. In the image, below, there are three layers, … ...
A linear mapping from a vector space to a field of scalars. In other words, a linear function which acts upon a vector … ...
Tensors Tensor Product
Bases Bases Transformation Coordinate Transformation Covectors Dual Space Identity Matrix Invertible Matrix Invertible …
A mapping from \(\mathbf{V} \rightarrow \mathbf{W}\) that preserves the operations of addition and scalar …
A function of several variables that is linear, separately, in each variable. A multilinear map of one variable is a …
The space of all linear functionals \(f:V\rightarrow \mathbb{R}\), noted as \(V^{*}\) The dual space has the same …