Machine Learning

with Functional Programming and F#

Evelina Gabasova (@evelgab)

F# for Machine Learning

"F# empowers users to tackle complex computing problems with simple, maintainable and robust code."

What this really means

• Can implement complex ML algorithms
• Code is easy to understand
• We can integrate it with .NET

Recognizing languages

Recognizing languages

What is the language of this text?

A Csillagok haboruja egy uropera filmsorozatnak, irodalmi muveknek es szamitogepes jatekoknak a neve.

This is Hungarian, of course!

What you won't learn

• how to use machine learning frameworks

PART 1

Recognizing languages using letter pair frequency

The plan

• Get sample text from from Wikipedia pages (done)

• Calculate features frequencies of letter pairs

• Compare languages using their features

• Classify language find the most similar one

STEP 1

Calculating frequencies

Example using sample English text "the three"

_t

2

th

2

he

1

e_

2

hr

1

re

1

ee

1

STEP 1

Calculating frequencies

Now calculate probabilities of the pairs

_t

0.2

th

0.2

he

0.1

e_

0.2

hr

0.1

re

0.1

ee

0.1

STEP 2

Calculating distance between features

th

e_

ee

el

English

0.3

0.2

0.2

0.1

Portuguese

0.0

0.2

0.1

0.3

Distance is the sum of squares of differences.

STEP 2

Calculating distance between features

th

e_

ee

el

English

0.3

0.2

0.2

0.1

Portuguese

0.0

0.2

0.1

0.3

Difference

0.3

0.0

0.1

-0.2

Sum of squares: \(0.09+0.0+0.01+0.04 = 0.14\)

STEP 3

Classifying unknown text

English

Spanish

Portuguese

Czech

Unknown text

0.10

0.14

0.25

0.27

PART 1

github.com/evelinag/LanguageRecognizer

PART 2

Recognizing languages using simple neural net

How neural networks work

Network with single neuron

Sigmoid function

\(f(x) = \frac{1}{1 + e^{-x}}\)

Learning the weights

• Initial weights can be generated randomly

• Improve weights using gradient descent

• Repeat recursively until certain error or number of steps

Improving using gradient descent

Gradient descent in more dimensions

Conclusions

Learning more

Learning more

• The F# Foundation www.fsharp.org

• FsLab Package www.fslab.org

• Accord.NET accord-framework.net
• Diffsharp library diffsharp.github.io/DiffSharp
• Hype library for deep learning hypelib.github.io/Hype
• Vulpes: deep belief networks github.com/fsprojects/Vulpes

Thank you!