From chatbots to your home thermostat, it seems like machine learning algorithms are everywhere nowadays. How about understanding how this works now? In this talk, you will learn about the basics of machine learning through various basic examples, without the need for a PhD or deep knowledge of assembly. At the end of this talk, you will know what the Naive Bayes classifiers, sentiment analysis and basic genetic algorithms are and how they work. You will also see how to create your own implementations in Javascript.

1. Learning Machine
Learning
A little intro to a (not that complex) world

2. @joel__lord
#phpworld
About Me
@joel__lord
joellord

3. @joel__lord
#phpworld
Our Agenda for today…
• AI vs ML
• Deep Learning &
Neural Networks
• Supervised vs
unsupervised
• Naïve Bayes Classifier
• Genetic Algorithms

4. @joel__lord
#phpworld

5. @joel__lord
#phpworld
Artificial Intelligence
Artificial intelligence (AI)
is intelligence exhibited by machines.
In computer science, the field of AI
research defines itself as the study of
"intelligent agents": any device that
perceives its environment and takes actions
that maximize its chance of success at
some goal.

6. @joel__lord
#phpworld
Artificial Intelligence
“takes actions that
maximize its chance of
success at some goal”

7. @joel__lord
#phpworld
Examples in real life

8. @joel__lord
#phpworld
Machine Learning
Machine learning (ML) is the subfield
of computer science that gives "computers
the ability to learn without being explicitly
programmed."

9. @joel__lord
#phpworld

10. @joel__lord
#phpworld

11. @joel__lord
#phpworld

12. @joel__lord
#phpworld

13. @joel__lord
#phpworld

14. @joel__lord
#phpworld
“Don’t be afraid of artificial
intelligence, be afraid of humanity.”

15. @joel__lord
#phpworld
Deep Learning
& Big Data
• Explosion of digital data
• Can’t be processed with
traditional methods
anymore

16. @joel__lord
#phpworld
Neural
Networks
• Breaking big
problems in small
layers
• Making connections

17. @joel__lord
#phpworld
Supervised
Learning
• Requires feedback
• Starts with nothing
and increases its
understanding
• Useless if the data
is of bad quality
• Use cases:
• Classification

18. @joel__lord
#phpworld
Unsupervised
Learning
• There is no feedback
• Good in the case of no right or
wrong answer
• Helps to identify patterns or data
structures
• Use case:
• You might also be interested
in…
• Grouping customers by
purchasing behaviors

19. @joel__lord
#phpworld
The Naïve Bayes Classifier

20. @joel__lord
#phpworld
Bayes Theorem

21. @joel__lord
#phpworld
Bayes Theorem
where

22. @joel__lord
#phpworld
Bayes Theorem
•

23. @joel__lord
#phpworld
Bayes Theorem
•

24. @joel__lord
#phpworld
Naive Bayes
Classifier
• Let’s look at a concrete
example.
• You never know what
you’re gonna get

25. @joel__lord
#phpworld
Probability that a chocolate has nuts
Nuts No Nuts
Round 25% 75%
Square 75% 25%
Dark 10% 90%
Light 90% 10%

26. @joel__lord
#phpworld
Do round, light chocolates have nuts?
Nuts No Nuts
Round 25% 75% 0.25 0.75
Square 75% 25% - -
Dark 10% 90% - -
Light 90% 10% 0.9 0.1

27. @joel__lord
#phpworld
Do round, light chocolates have nuts?
Nuts No Nuts
Round 25% 75% 0.25 0.75
Square 75% 25% - -
Dark 10% 90% - -
Light 90% 10% 0.9 0.1
0.225 0.075

28. @joel__lord
#phpworld
Do round, light chocolates have nuts?
Nuts No Nuts
Round 25% 75% 0.25 0.75
Square 75% 25% - -
Dark 10% 90% - -
Light 90% 10% 0.9 0.1
0.225 0.075

29. @joel__lord
#phpworld
Naïve Bayes Classifier in code
var Classifier = function() {
this.dictionaries = {};
};
Classifier.prototype.classify = function(text, group) {
};
Classifier.prototype.categorize = function(text) {
};

30. @joel__lord
#phpworld

31. @joel__lord
#phpworld
Sentiment
Analysis
• Not Machine
Learning
• Uses classifiers and
AFINN-165 (and
emojis)

32. @joel__lord
#phpworld
Sentiment
Analysis
• Javascript:
• npm install
sentiment
• PHP:
• composer require
risan/sentiment-
analysis

33. @joel__lord
#phpworld
Genetic
Algorithm
• Awesome shit!

34. @joel__lord
#phpworld
Genetic
Algorithm
• Create a population of
random individuals
• Keep the closest individuals
• Keep a few random
individuals
• Introduce random
mutations
• Randomly create ”children”
• Magically end up with a
valid solution

35. @joel__lord
#phpworld
Genetic
Algorithm
• Create a population of
random individuals
• Keep the closest individuals
• Keep a few random
individuals
• Introduce random
mutations
• Randomly create ”children”
• Magically end up with a
valid solution

36. @joel__lord
#phpworld
Genetic Algorithm
Credit: AutoDesk https://autodeskresearch.com/projects/
Dreamcatcher

37. @joel__lord
#phpworld
https://www.youtube.com/watch?v=pgaEE27nsQw

38. @joel__lord
#phpworld
Boring!

39. @joel__lord
#phpworld

40. @joel__lord
#phpworld
Genetic Algorithm in code
//Declare Consts
function randomInt(min, max) {…}
function random(min, max) {…}
function fitness(individual) {…}
function sortByFitness(population) {…}
function randomIndividual() {…}
function randomPopulation(size) {…}
function mutate(population) {…}
function reproduce(father, mother) {…}
function evolve(population) {…}
function findSolution() {
var population = randomPopulation(POP_SIZE);
var generation = 0;
while (fitness(population[0]) > CLOSE_ENOUGH) {
generation++;
population = evolve(population);
}
return {solution: population[0], generations: generation};
}
var sol = findSolution();

41. @joel__lord
#phpworld
What did we learn?
• Machine Learning and Artificial Intelligence
• Big Data and Deep Learning
• Supervised vs unsupervised
• Basic Algorithms
• Naïve Bayes Classifier
• Sentiment Analysis
• Genetic Algorithm

42. @joel__lord
#phpworld
What did we learn?
• Machine Learning and Artificial Intelligence
• Big Data and Deep Learning
• Supervised vs unsupervised
• Basic Algorithms
• Naïve Bayes Classifier
• Sentiment Analysis
• Genetic Algorithm
• Hopefully, you don’t feel intimidated by ML anymore

43. Presented By
JOEL LORD
php[world], November 15th, 2018
@joel__lord
joellord
Thank you!

44. Presented By
@joel__lord
joellord
Questions?
JOEL LORD
php[world], November 15th, 2018

45. Impact of parameters on Genetic Algorithms