Kotlin + Maths Dinorah Tovar @ddinorahtovar Google Developer Expert - Android Santo Domingo 

Disclaimer - I’m not a data science engineer 

Left Aligned Title Kotlin help us to solve many problems - but specially in maths! Math’s are coolest thing! • A fast operational language • Mathematical expressions • Algebraic data types (sealed class) • We can do simple functions - from basic to complex 

Simple quote or statement goes here. Ideally limit to four or five lines max. This function takes mseconds 258 fun main() { val y = complex(2, 1) var x = complex(0, 0) val time = measureTimeMillis { repeat(10000000) { x += y x *= y x -= y x /= y } } } 

Simple quote or statement goes here. Ideally limit to four or five lines max. This function takes seconds 2.76 def main(): z = complex(2, 1) w = complex(0, 0) start = time.time() for i in range(0, 10000000): w += z w *= z w -= z w /= z ende = time.time() 

9 times At least more efficient 

Mathematical expressions are pretty much pseudocode 

Left Aligned Title 2x + 10 First degree equation fun calc(x: Int) : Int { return 2*x + 10 } 

Left Aligned Title 10 ∑ i=1 1 i + 1 Summation val sum = 0 for (i in 1..10) { sum += 1/(i+1) } fun f() = (1..10).map { i -> 1 / (i + 1) }.sum() 

Left Aligned Title 3 ∏ i=1 i Product fun f() = (1..3).fold( 1L, Long::times) 

ADT is a type which is represented by several other subtypes 

Simple quote or statement goes here. Ideally limit to four or five lines max. ADT are only Class Sealed sealed class Tree data class Node( val value: T, val left: Tree = Empty, val right: Tree = Empty ) : Tree() 

Simple quote or statement goes here. Ideally limit to four or five lines max. ADT can create Sequences Nodes fun f() { val tree = Node( 10, 20, Node(40, 20, 10) ) // we can create ext function // and get the result } 

Algebraic operations 

Left Aligned Title {1,2,4,10} Average Max - Min fun f() { val seq = floatArrayOf( 1F, 2F, 4F, 10F ) val avg = seq.average() val max = seq.max() val min = seq.min() } 

Left Aligned Title ( 222 222 222 ) Multi- dimensional Vectors fun f() { val mx = arrayOf( arrayOf(floatArrayOf(2F, 2F, 2F)), arrayOf(floatArrayOf(2F, 2F, 2F)), arrayOf(floatArrayOf(2F, 2F, 2F)) ) val normArray = mx.map { column -> column.map { row -> row.map { element -> element / 255F } } } } 

Probability and Statistics 

Let’s solve a problem Let’s calculate the probability of the weather in the last week in Mexico City! Last week weather Partially Sunny Rainy Rainy Cloudy Partially Sunny 

Just rainy probability val weatherMexicoCity = arrayOf( "Partially Sunny", "Rainy" , "Partially Sunny" , "Cloudy", "Rainy" ) val rainyProbability = weatherMexicoCity.count { it == "Rainy" } / weatherMexicoCity.size 

How about all the weathers val weatherMexicoCity = arrayOf( "Partially Sunny", "Rainy" , "Partially Sunny" , "Cloudy", "Rainy" ) val generalProbability = weatherMexicoCity.map { label -> labels.count { it == label } / labels.size } 

Charts + Statistics 

Kotlin has integration for Notebooks - specifically for Jupiter 

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Kotlin + Maths Dinorah Tovar @ddinorahtovar Google Developer Expert - Android Santo Domingo