Machine Learning@2014

Un ouvrage de référence -emprunter à la bibliothèque-.

2014
 
Il y a 20 ans déjà...
 
1994

Un éternel recommencement dans la quête du SI parfait dans un monde imparfait. (*)

Machine Learning@2017

Learn MachineLearning as a Machine.

Apprentissage
Supervisé Non supervisé Par renforcement
Classification Régression Classification Régression
TODO TODO TODO 
dataset = loadtxt('dev/mlearn-09/data-0.txt')
...
model = XGBClassifier()
model.fit(x_train, y_train)
...
y_pred = model.predict(x_test)
accuracy = accuracy_score(y_test, y_pred)

bin/mahout org.cluster.syntheticctrl.kmeans.Job
bin/mahout org.cluster.syntheticctrl.fuzzykmeans.Job
...
2015... 1.0:[distance=60.31]:[26.2,48.1 ... 24.3,19.7]
...
2015... ClusterDumper: Wrote 6 clusters
2015... MahoutDriver: Program took 704709 ms

pip list --format=myFormat.






 
from httplib import *
import ssl
@1996 
from pyspark import SparkContext
from pyspark.streaming import StreamingContext
from pyspark.sql import SparkSession
@2016
     
from qgis.core import *
import gdal
import qgis.utils
from PyQt4.QtCore import QFile, QFileInfo, QVariant


@201[6,7] 
from xgboost import XGBClassifier
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score


dataset = loadtxt('data')
...
model = XGBClassifier()
model.fit(x_trn, y_trn)
...
y_pred = model.predict(x_tst)
accuracy_score(y_test, y_prd)
@2017 
from flask import Flask
@2002 
import matplotlib.pyplot as Pyplt
from matplotlib.patches import Polygon
from matplotlib.patches import Patch
from matplotlib import animation, rc

@1992

TODO: ])]))]))]))]), (*)