## #Basics

**Combinations**
{
⸢Math⸥
}
[
#Combinations
#Basics
]

## #Bayesian

**Bayes' Theorem**
{
⸢Math⸥
}
[
#Statistics
#Bayesian
]

## #Combinations

**Combinations**
{
⸢Math⸥
}
[
#Combinations
#Basics
]

## #Distance

**Cosine Similarity**
{
⸢Math⸥
}
[
#Set
#Distance
]

**Jaccard Similarity**
{
⸢Math⸥
}
[
#Set
#Distance
]

**Levenshtein Distance**
{
⸢Math⸥
}
[
#Distance
#NLP
]

## #Factorization

**Canonical Decomposition**
{
⸢Math⸥
}
[
#Tensor
#Factorization
#Linear Algebra
]

**SVD: Singular Value Decomposition**
{
⸢Math⸥
}
[
#Matrix
#Factorization
#Linear Algebra
]

**Tucker Decomposition**
{
⸢Math⸥
}
[
#Tensor
#Factorization
#Linear Algebra
]

## #Linear Algebra

**Canonical Decomposition**
{
⸢Math⸥
}
[
#Tensor
#Factorization
#Linear Algebra
]

**SVD: Singular Value Decomposition**
{
⸢Math⸥
}
[
#Matrix
#Factorization
#Linear Algebra
]

**Tucker Decomposition**
{
⸢Math⸥
}
[
#Tensor
#Factorization
#Linear Algebra
]

## #Matrix

## #NLP

**Term Frequency - Inverse Document Frequency**
{
⸢Math⸥
}
[
#NLP
]

**Levenshtein Distance**
{
⸢Math⸥
}
[
#Distance
#NLP
]

## #Set

**Cosine Similarity**
{
⸢Math⸥
}
[
#Set
#Distance
]

**Jaccard Similarity**
{
⸢Math⸥
}
[
#Set
#Distance
]

## #Statistics

**Bayes' Theorem**
{
⸢Math⸥
}
[
#Statistics
#Bayesian
]

## #Tensor

**Canonical Decomposition**
{
⸢Math⸥
}
[
#Tensor
#Factorization
#Linear Algebra
]

**Modes and Slices of Tensors**
{
⸢Math⸥
}
[
#Tensor
]

**Tucker Decomposition**
{
⸢Math⸥
}
[
#Tensor
#Factorization
#Linear Algebra
]