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Learning Machine
Learning
A little intro to a (not that complex) world
@joel__lord
#phpworld
About Me
@joel__lord
joellord
@joel__lord
#phpworld
Our Agenda for today…
• AI vs ML
• Deep Learning &
Neural Networks
• Supervised vs
unsupervised
• Na...
@joel__lord
#phpworld
@joel__lord
#phpworld
Artificial Intelligence
Artificial intelligence (AI)
is intelligence exhibited by machines.
In compu...
@joel__lord
#phpworld
Artificial Intelligence
“takes actions that
maximize its chance of
success at some goal”
@joel__lord
#phpworld
Examples in real life
@joel__lord
#phpworld
Machine Learning
Machine learning (ML) is the subfield
of computer science that gives "computers
the...
@joel__lord
#phpworld
@joel__lord
#phpworld
@joel__lord
#phpworld
@joel__lord
#phpworld
@joel__lord
#phpworld
@joel__lord
#phpworld
“Don’t be afraid of artificial
intelligence, be afraid of humanity.”
@joel__lord
#phpworld
Deep Learning
& Big Data
• Explosion of digital data
• Can’t be processed with
traditional methods
a...
@joel__lord
#phpworld
Neural
Networks
• Breaking big
problems in small
layers
• Making connections
@joel__lord
#phpworld
Supervised
Learning
• Requires feedback
• Starts with nothing
and increases its
understanding
• Usel...
@joel__lord
#phpworld
Unsupervised
Learning
• There is no feedback
• Good in the case of no right or
wrong answer
• Helps ...
@joel__lord
#phpworld
The Naïve Bayes Classifier
@joel__lord
#phpworld
Bayes Theorem
@joel__lord
#phpworld
Bayes Theorem
where
@joel__lord
#phpworld
Bayes Theorem
•  
@joel__lord
#phpworld
Bayes Theorem
•  
@joel__lord
#phpworld
Naive Bayes
Classifier
• Let’s look at a concrete
example.
• You never know what
you’re gonna get
@joel__lord
#phpworld
Probability that a chocolate has nuts
Nuts No Nuts
Round 25% 75%
Square 75% 25%
Dark 10% 90%
Light 9...
@joel__lord
#phpworld
Do round, light chocolates have nuts?
Nuts No Nuts
Round 25% 75% 0.25 0.75
Square 75% 25% - -
Dark 1...
@joel__lord
#phpworld
Do round, light chocolates have nuts?
Nuts No Nuts
Round 25% 75% 0.25 0.75
Square 75% 25% - -
Dark 1...
@joel__lord
#phpworld
Do round, light chocolates have nuts?
Nuts No Nuts
Round 25% 75% 0.25 0.75
Square 75% 25% - -
Dark 1...
@joel__lord
#phpworld
Naïve Bayes Classifier in code
var Classifier = function() {
this.dictionaries = {};
};
Classifier.p...
@joel__lord
#phpworld
@joel__lord
#phpworld
Sentiment
Analysis
• Not Machine
Learning
• Uses classifiers and
AFINN-165 (and
emojis)
@joel__lord
#phpworld
Sentiment
Analysis
• Javascript:
• npm install
sentiment
• PHP:
• composer require
risan/sentiment-
...
@joel__lord
#phpworld
Genetic
Algorithm
• Awesome shit!
@joel__lord
#phpworld
Genetic
Algorithm
• Create a population of
random individuals
• Keep the closest individuals
• Keep ...
@joel__lord
#phpworld
Genetic
Algorithm
• Create a population of
random individuals
• Keep the closest individuals
• Keep ...
@joel__lord
#phpworld
Genetic Algorithm
Credit: AutoDesk https://autodeskresearch.com/projects/
Dreamcatcher
@joel__lord
#phpworld
https://www.youtube.com/watch?v=pgaEE27nsQw
@joel__lord
#phpworld
Boring!
@joel__lord
#phpworld
@joel__lord
#phpworld
Genetic Algorithm in code
//Declare Consts
function randomInt(min, max) {…}
function random(min, max...
@joel__lord
#phpworld
What did we learn?
• Machine Learning and Artificial Intelligence
• Big Data and Deep Learning
• Sup...
@joel__lord
#phpworld
What did we learn?
• Machine Learning and Artificial Intelligence
• Big Data and Deep Learning
• Sup...
Presented By
JOEL LORD
php[world], November 15th, 2018
@joel__lord
joellord
Thank you!
Presented By
@joel__lord
joellord
Questions?
JOEL LORD
php[world], November 15th, 2018
Impact of parameters on Genetic Algorithms
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Learning Machine Learning

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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.

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Learning Machine Learning

  1. 1. Learning Machine Learning A little intro to a (not that complex) world
  2. 2. @joel__lord #phpworld About Me @joel__lord joellord
  3. 3. @joel__lord #phpworld Our Agenda for today… • AI vs ML • Deep Learning & Neural Networks • Supervised vs unsupervised • Naïve Bayes Classifier • Genetic Algorithms
  4. 4. @joel__lord #phpworld
  5. 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. 6. @joel__lord #phpworld Artificial Intelligence “takes actions that maximize its chance of success at some goal”
  7. 7. @joel__lord #phpworld Examples in real life
  8. 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. 9. @joel__lord #phpworld
  10. 10. @joel__lord #phpworld
  11. 11. @joel__lord #phpworld
  12. 12. @joel__lord #phpworld
  13. 13. @joel__lord #phpworld
  14. 14. @joel__lord #phpworld “Don’t be afraid of artificial intelligence, be afraid of humanity.”
  15. 15. @joel__lord #phpworld Deep Learning & Big Data • Explosion of digital data • Can’t be processed with traditional methods anymore
  16. 16. @joel__lord #phpworld Neural Networks • Breaking big problems in small layers • Making connections
  17. 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. 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. 19. @joel__lord #phpworld The Naïve Bayes Classifier
  20. 20. @joel__lord #phpworld Bayes Theorem
  21. 21. @joel__lord #phpworld Bayes Theorem where
  22. 22. @joel__lord #phpworld Bayes Theorem •  
  23. 23. @joel__lord #phpworld Bayes Theorem •  
  24. 24. @joel__lord #phpworld Naive Bayes Classifier • Let’s look at a concrete example. • You never know what you’re gonna get
  25. 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. 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. 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. 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. 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. 30. @joel__lord #phpworld
  31. 31. @joel__lord #phpworld Sentiment Analysis • Not Machine Learning • Uses classifiers and AFINN-165 (and emojis)
  32. 32. @joel__lord #phpworld Sentiment Analysis • Javascript: • npm install sentiment • PHP: • composer require risan/sentiment- analysis
  33. 33. @joel__lord #phpworld Genetic Algorithm • Awesome shit!
  34. 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. 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. 36. @joel__lord #phpworld Genetic Algorithm Credit: AutoDesk https://autodeskresearch.com/projects/ Dreamcatcher
  37. 37. @joel__lord #phpworld https://www.youtube.com/watch?v=pgaEE27nsQw
  38. 38. @joel__lord #phpworld Boring!
  39. 39. @joel__lord #phpworld
  40. 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. 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. 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. 43. Presented By JOEL LORD php[world], November 15th, 2018 @joel__lord joellord Thank you!
  44. 44. Presented By @joel__lord joellord Questions? JOEL LORD php[world], November 15th, 2018
  45. 45. Impact of parameters on Genetic Algorithms

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.

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