Apprendre l'apprentissage automatisé

www.spiria.com

Apprendre l’apprentissage automatisé

Présenté par

JOEL LORD

Web à Québec4 avril, 2017

@joel__lord#WAQ17

JOEL LORDÀ propos de moi

• Adorateur de Javascript• Bidouilleur• Enthousiaste des

technologies

@joel__lord#WAQ17

Agenda

• Intelligence articifielle vs Apprentissage automatisé• Big Data et apprentissage profond• Les algo de base

• Naïve Bayes Classifier• Sentiment Analysis• Genetic Algorithm

@joel__lord#WAQ17

Agenda

• Intelligence articifielle vs Apprentissage automatisé• Big Data et apprentissage profond• Les algo de base

• Naïve Bayes Classifier• Sentiment Analysis• Genetic Algorithm

• Le tout parsemé de démos

Intelligence Articielle et Apprentissage automatisé

UN PEU PLUS AU SUJET DE…

@joel__lord#WAQ17

Intelligence artificielleQU’EST CE QUI EN EST

@joel__lord#WAQ17

L'intelligence artificielle (IA) estl'intelligence fournie par les machines. Eninformatique, le domaine de la recherchesur l'IA se définit comme l'étude des «agents intelligents»: tout dispositif qui perçoit son environnement et prend des mesures qui maximisent ses chances de succès à un but.

@joel__lord#WAQ17

Intelligence ArtificielleEXEMPLES CONCRETS

@joel__lord#WAQ17

Intelligence ArtificielleEXEMPLES CONCRETES

• Filtres de pouriels

@joel__lord#WAQ17


• Filtres de polluriels• Prévention de la fraude

@joel__lord#WAQ17


• Filtres de polluriels• Prévention de la fraude• Reconnaissance faciale

@joel__lord#WAQ17

L'apprentissage automatisé est le sous-domaine de l'informatique qui donne aux «ordinateurs la possibilité d'apprendresans être explicitement programmés».

@joel__lord#WAQ17

Apprentissage automatiséEXEMPLES CONCRETS

• Thermostats intelligents

@joel__lord#WAQ17


• Thermostats intelligents• Cortana, Siri et Ok Google

@joel__lord#WAQ17


• Thermostats intelligents• Cortana, Siri et Ok Google• Chat Bots

@joel__lord#WAQ17



@joel__lord#WAQ17



@joel__lord#WAQ17



@joel__lord#WAQ17



@joel__lord#WAQ17



@joel__lord#WAQ17



Big Data et apprentissageprofond

ENCORE UN PEU DE THÉORIE

@joel__lord#WAQ17

Big DataQU’EST-CE QUE C’EST?

• Croissanceexponentielle des données digitales

• Trop complexe à traiterde façon traditionnelle

• Principalement utiliséepour de la prédictionou analyse des comportements des utilisateurs

@joel__lord#WAQ17

Apprentissage profonD (Deep learning)QU’EST-CE QUE C’EST

• Utilise des réseaux neuronaux pour traiter les données• Idéal pour des classsificateurs complexes• Un moyen de traiter le big data

@joel__lord#WAQ17

Réseaux NeuronauxEUH…. WHAT?

• Une collection de couches d’opérations

• Déconstruction d’uneproblème complexe entâches plus simples

Supervisé vs non-superviséUNE DERNIÈRE PETITE CHOSE…

@joel__lord#WAQ17

Apprentissage superviséQU’EST-CE QUE C’EST

• Requiert une rétroaction• Débute avec aucune connaissance et augmente sa compréhension• Inutile lorsque les données sont de mauvaise qualité• Cas pratiques

• Classification

@joel__lord#WAQ17

Apprentissage non-superviséCONTRAIRE DE SUPERVISÉ?

• Besoin d’aucun feedback• Pratique lorsqu’il n’y a pas de bonne ou mauvais réponse• Aide à trouver des patterns ou structures de données• Cas pratiques

• “Vous pourriez aussi être intéressé par…”• Grouper des clients selon leur comportement

Apprentissage automatiséDE RETOUR À LA PROGRAMMATION NORMALE

@joel__lord#WAQ17

Classification naïve bayésienneDÉFINITION

• Algorithme supervisé• Un simple moyen de classifier et identifier l’information

var classifier = new Classifier();classifier.classify("J'adore le Javascript", POSITIVE);classifier.classify('WebStorm est génial', POSITIVE);classifier.classify('Non, Javascript est mauvais', NEGATIVE);classifier.classify("Je n'aime pas le brocoli", NEGATIVE);

console.log(classifier.categorize("Javascript est génial"));// "positive"

console.log(classifier.categorize("J'aime WebStorm"));// undefined

@joel__lord#WAQ17

Classification naïve bayésienneDÉFINITION

• Algorithme supervisé• Un simple moyen de classifier et identifier l’information• Mathématiquement exprimé par la fonction suivante

@joel__lord#WAQ17

Classification naïve bayésienneDÉFINITION DE LA STRUCTURE

var Classifier = function() {this.dictionaries = {};};

Classifier.prototype.classify = function(text, group) {

};

Classifier.prototype.categorize = function(text) {

};

@joel__lord#WAQ17

Classification naïve bayésienneCRÉATION DE LA CLASSIFICATION

Classifier.prototype.classify = function(text, group) {var words = text.split(" ");this.dictionaries[group] ? "" : this.dictionaries[group] = {};

var self = this;words.map((w) => {if (self.dictionaries[group][w]) {self.dictionaries[group][w]++;} else {self.dictionaries[group][w] = 1;}});};

@joel__lord#WAQ17

Classification naïve bayésienneET LE RESTE…Classifier.prototype.categorize = function(text) {var self = this;var probabilities = {};var groups = [];var finals = {};//Find the groupsfor (var k in this.dictionaries) {groups.push(k);}var sums = {};var probs = {};//Loop through the groups to calculate the sums of found textfor (var j = 0; j < groups.length; j++) {if (!sums[text]) sums[text] = 0;if (!this.dictionaries[groups[j]][text]) this.dictionaries[groups[j]][text] = 0;sums[text] += this.dictionaries[groups[j]][text];probs[groups[j]] = (this.dictionaries[groups[j]][text]) ? this.dictionaries[groups[j]][text] : 0;}// Perform calculationsfor (var j = 0; j < groups.length; j++) {(!probabilities[text]) ? probabilities[text] = {} : "";(!probs[groups[j]]) ? probabilities[text][groups[j]] = 0 : probabilities[text][groups[j]] =

probs[groups[j]]/sums[text];}//Average out the probabilities

for (var j = 0; j < groups.length; j++) {if (!finals[groups[j]]) finals[groups[j]] = [];finals[groups[j]].push(probabilities[text][groups[j]]);}for (var i = 0; i < groups.length; i++) {finals[groups[i]] = average(finals[groups[i]]);}//Find the largest probabilityvar highestGroup = "";var highestValue = 0;for (var group in finals) {if (finals[group] > highestValue) {highestGroup = group;highestValue = finals[group];}}

return highestGroup;};

@joel__lord#WAQ17

Classification naïve bayésienneCATÉGORISATION

Classifier.prototype.categorize = function(text) {var self = this;var probabilities = {};var groups = [];var finals = {};

};

@joel__lord#WAQ17


Classifier.prototype.categorize = function(text) {…//Find the groupsfor (var k in this.dictionaries) {groups.push(k);}var sums = {};var probs = {};

};

@joel__lord#WAQ17


Classifier.prototype.categorize = function(text) {…//Loop through the groups to calculate the sums of found textfor (var j = 0; j < groups.length; j++) {if (!sums[text]) sums[text] = 0;if (!this.dictionaries[groups[j]][text]) this.dictionaries[groups[j]][text]

= 0;sums[text] += this.dictionaries[groups[j]][text];probs[groups[j]] = (this.dictionaries[groups[j]][text]) ?

this.dictionaries[groups[j]][text] : 0;}};

@joel__lord#WAQ17


Classifier.prototype.categorize = function(text) {…// Perform calculationsfor (var j = 0; j < groups.length; j++) {(!probabilities[text]) ? probabilities[text] = {} : "";(!probs[groups[j]]) ? probabilities[text][groups[j]] = 0 :

probabilities[text][groups[j]] = probs[groups[j]]/sums[text];}};

@joel__lord#WAQ17


Classifier.prototype.categorize = function(text) {…

//Average out the probabilities

for (var j = 0; j < groups.length; j++) {if (!finals[groups[j]]) finals[groups[j]] = [];finals[groups[j]].push(probabilities[text][groups[j]]);

}for (var i = 0; i < groups.length; i++) {finals[groups[i]] = average(finals[groups[i]]);

}};

@joel__lord#WAQ17


Classifier.prototype.categorize = function(text) {…//Find the largest probabilityvar highestGroup = "";var highestValue = 0;for (var group in finals) {if (finals[group] > highestValue) {highestGroup = group;highestValue = finals[group];

}}


@joel__lord#WAQ17

Classification naïve bayésienneSOMMAIREClassifier.prototype.categorize = function(text) {var self = this;var probabilities = {};var groups = [];var finals = {};//Find the groupsfor (var k in this.dictionaries) {groups.push(k);}var sums = {};var probs = {};//Loop through the groups to calculate the sums of found textfor (var j = 0; j < groups.length; j++) {if (!sums[text]) sums[text] = 0;if (!this.dictionaries[groups[j]][text]) this.dictionaries[groups[j]][text] = 0;sums[text] += this.dictionaries[groups[j]][text];probs[groups[j]] = (this.dictionaries[groups[j]][text]) ? this.dictionaries[groups[j]][text] : 0;}// Perform calculationsfor (var j = 0; j < groups.length; j++) {(!probabilities[text]) ? probabilities[text] = {} : "";(!probs[groups[j]]) ? probabilities[text][groups[j]] = 0 : probabilities[text][groups[j]] =

probs[groups[j]]/sums[text];}//Average out the probabilities

for (var j = 0; j < groups.length; j++) {if (!finals[groups[j]]) finals[groups[j]] = [];finals[groups[j]].push(probabilities[text][groups[j]]);}for (var i = 0; i < groups.length; i++) {finals[groups[i]] = average(finals[groups[i]]);}//Find the largest probabilityvar highestGroup = "";var highestValue = 0;for (var group in finals) {if (finals[group] > highestValue) {highestGroup = group;highestValue = finals[group];}}


Montrez moi !CLASSIFICATION NAÏVE BAYÉSIENNE

@joel__lord#WAQ17

Analyse de sentimentsCOMMENT ÇA FONCTIONNE

• Approche similaire aux classificateurs• Utilise une liste de mots (AFINN-165) et parfois les emoticons pour

donner un score.

@joel__lord#WAQ17

Analyse de sentimentsEXEMPLE DE CODE

var twit = require("twit");var sentiment = require("sentiment");

@joel__lord#WAQ17


var keyword = "#waq17";var t = new twit(require("./credentials"));var stream1 = t.stream("statuses/filter", {track: keyword});

@joel__lord#WAQ17


stream1.on("tweet", function (tweet) {

});

@joel__lord#WAQ17


var score = sentiment(tweet.text);console.log("--- \n New Tweet\n" + tweet.text + "\n" + (score > 0 ?

"Positive" : "Negative"));

@joel__lord#WAQ17


var twit = require("twit");var sentiment = require("sentiment");var keyword = "#waq17";var t = new twit(require("./credentials"));var stream1 = t.stream("statuses/filter", {track: keyword});stream1.on("tweet", function (tweet) {var score = sentiment(tweet.text);console.log("--- \n New Tweet\n" + tweet.text + "\n" + (score > 0 ?

"Positive" : "Negative"));});

Montrez moi !ANALYSE DE SENTIMENTS

@joel__lord#WAQ17

Algorithmes génétiquesÇA MANGE QUOI EN HIVER

• Moyen de trouver une solution idéaleen utilisant des solutions aléatoires

• Cas pratiques• Moteurs d’avion• Hackrod

@joel__lord#WAQ17

Algorithmes génétiquesCOMMENT ÇA FONCTIONNE

• On crée une population d’individus aléatoires• On garde les plus proches de la solution• On garde des individus aléatoires• On introduit des mutations aléatores• On crée aléatoirement des “enfants”• On arrive magiquement à une solution!

@joel__lord#WAQ17

Algorithmes génétiquesCOMMENT ÇA FONCTIONNE

• On crée une population d’individus aléatoires• On garde les plus proches de la solution• On garde des individus aléatoires• On introduit des mutations aléatores• On crée aléatoirement des “enfants”• On arrive magiquement à une solution!

@joel__lord#WAQ17

Algorithmes génétiquesL’IMPORTANCE DES MUTATIONS

@joel__lord#WAQ17

Algorithmes génétiquesEXEMPLE DE CODE

var population = [];const TARGET = 200;const MIN = 0;const MAX = TARGET - 1;const IND_COUNT = 4;const POP_SIZE = 100;const CLOSE_ENOUGH = 0.001;var RETAIN = 0.02;var RANDOM_SELECTION = 0.05;var MUTATION_PROBABILITY = 0.01;

@joel__lord#WAQ17


//Declare Consts

function randomInt(min, max) {return Math.round(random(min, max));

}

function random(min, max) {if (max == undefined) { max = min; min = 0; }if (max == undefined) { max = 100; }return (Math.random()*(max-min)) + min;

}

@joel__lord#WAQ17


//Declare Constsfunction randomInt(min, max) {…}function random(min, max) {…}

function fitness(individual) {sum = individual.reduce((a,b) => a + b, 0);return Math.abs(TARGET - sum);

}

function sortByFitness(population) {population.sort((a, b) => {var fitA = fitness(a); var fitB = fitness(b);return fitA > fitB ? 1 : -1;

});return population;

}

@joel__lord#WAQ17


//Declare Constsfunction randomInt(min, max) {…}function random(min, max) {…}function fitness(individual) {…}function sortByFitness(population) {…}

function randomIndividual() {var individual = [];for (var i = 0; i < IND_COUNT; i++) {individual.push(random(MIN, MAX));

}return individual;

}

function randomPopulation(size) {var population = [];for (var i = 0; i < size; i++) {population.push(randomIndividual());

}return population;

}

@joel__lord#WAQ17


//Declare Constsfunction randomInt(min, max) {…}function random(min, max) {…}function fitness(individual) {…}function sortByFitness(population) {…}function randomIndividual() {…}function randomPopulation(size) {…}

function mutate(population) {for (var i=0; i < population.length; i++) {if (MUTATION_PROBABILITY > Math.random()) {var index = randomInt(population[i].length);population[i][index] = random(MIN, MAX);

}}return population;

}

@joel__lord#WAQ17


//Declare Constsfunction 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) {var half = father.length / 2;var child = [];child = child.concat(father.slice(0, half), mother.slice(half,

mother.length));return child;

}

@joel__lord#WAQ17


//Declare Constsfunction 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) {var parents = [];//Keep the best solutionsparents=sortByFitness(population).slice(0,Math.round(POP_SIZE*RETAIN));//Randomly add new elementsfor (var i = parents.length; i < POP_SIZE - parents.length; i++) {if (RANDOM_SELECTION > Math.random()) {parents.push(randomIndividual());

}}

}

@joel__lord#WAQ17


//Declare Constsfunction 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) {//Random Stuffparents = mutate(parents);var rndMax = parents.length - 1;while (parents.length < POP_SIZE) {var father = randomInt(rndMax);var mother = randomInt(rndMax);if (father != mother) {father = parents[father]; mother = parents[mother];parents.push(reproduce(father, mother));

}}return parents;

}

@joel__lord#WAQ17


//Declare Constsfunction 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();

@joel__lord#WAQ17


var population = [];const TARGET = 200;const MIN = 0;const MAX = TARGET - 1;const IND_COUNT = 4;const POP_SIZE = 100;const CLOSE_ENOUGH = 0.001;var RETAIN = 0.02;var RANDOM_SELECTION = 0.05;var MUTATION_PROBABILITY = 0.01;

function randomInt(min, max) {return Math.round(random(min, max));

}

function random(min, max) {if (max == undefined) { max = min; min = 0; }if (max == undefined) { max = 100; }return (Math.random()*(max-min)) + min;

}

function fitness(individual) {sum = individual.reduce((a,b) => a + b, 0);return Math.abs(TARGET - sum);

}

function sortByFitness(population) {population.sort((a, b) => {var fitA = fitness(a); var fitB = fitness(b);return fitA > fitB ? 1 : -1;

});return population;

}

function randomIndividual() {var individual = [];for (var i = 0; i < IND_COUNT; i++) {individual.push(random(MIN, MAX));

}return individual;

}

function randomPopulation(size) {var population = [];for (var i = 0; i < size; i++) {population.push(randomIndividual());

}return population;

}

function mutate(population) {for (var i=0; i < population.length; i++) {if (MUTATION_PROBABILITY > Math.random()) {var index = randomInt(population[i].length);population[i][index] = random(MIN, MAX);

}}return population;

}

function reproduce(father, mother) {var half = father.length / 2;var child = [];child = child.concat(father.slice(0, half), mother.slice(half, mother.length));return child;

}

function evolve(population) {var parents = [];//Keep the best solutionsparents = sortByFitness(population).slice(0, Math.round(POP_SIZE*RETAIN));//Randomly add new elementsfor (var i = parents.length; i < POP_SIZE - parents.length; i++) {if (RANDOM_SELECTION > Math.random()) {parents.push(randomIndividual());

}}//Mutate elementsparents = mutate(parents);var rndMax = parents.length - 1;while (parents.length < POP_SIZE) {var father = randomInt(rndMax);var mother = randomInt(rndMax);if (father != mother) {father = parents[father];mother = parents[mother];parents.push(reproduce(father, mother));

}}return parents;

}

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();console.log("Found solution in " + sol.generations + " generations.", sol.solution);

Faut le voir pour le croireALGORITHMES GÉNÉTIQUES

DOCUMENT CONFIDENTIEL, TOUT DROIT RÉSERVÉ

PRESENTED BY

That’s all folks !Questions?

JOEL LORDApril 4th, 2017

TWITTER: @JOEL__LORDGITHUB: HTTP://GITHUB.COM/JOELLORD

@joel__lord#WAQ17

QuestionIMPACT OF PARAMETERS ON GENETIC ALGORITHMS

Internet

Apprendre l'apprentissage automatisé