Tag Archive for "Python" - Antoine ARTAUD

nov

python datascience startup

Posted by : admin | On : 9 novembre 2017

Tags:and demonstrate the basic functionality of the IPython Notebook. If you don't yet know any Python, datascience, I'll also provide four recommended resources for learning Python. This is the second video in the series: "Introduction to machine learning with scikit-learn". Read more about this video here: http://, Python, show how to install my preferred Python distribution, Want to get started with machine learning in Python? I'll discuss the pros and cons of the scikit-learn library

https://github.com/justmarkham/scikit-learn-videos

https://www.class-central.com/mooc/835/coursera-machine-learning

https://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/courseware/f6eb0a2902904c6e8f74a2c15833d1ad/97f87bf36b4a4eeb90e1ca1171fb6750/

https://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/ba1951b8f66c4cdca2fcaabcdc91b792/

rWant to get started with machine learning in Python? I’ll discuss the pros and cons of the scikit-learn library, show how to install my preferred Python distribution, and demonstrate the basic functionality of the IPython Notebook. If you don’t yet know any Python, I’ll also provide four recommended resources for learning Python.

This is the second video in the series: « Introduction to machine learning with scikit-learn ». Read more about this video here:
http://blog.kaggle.com/2015/04/15/sci…

The IPython notebook shown in the video is available on GitHub:
https://github.com/justmarkham/scikit…

== RESOURCES ==
Six reasons why I recommend scikit-learn: http://radar.oreilly.com/2013/12/six-…
API design for machine learning software: http://arxiv.org/pdf/1309.0238v1.pdf
Should you teach Python or R for data science?: http://www.dataschool.io/python-or-r-…
scikit-learn installation: http://scikit-learn.org/stable/instal…
Anaconda installation: https://store.continuum.io/cshop/anac…
IPython installation: http://ipython.org/install.html
nbviewer: http://nbviewer.ipython.org/
IPython documentation: http://ipython.org/ipython-doc/stable…
IPython Notebook tutorials: http://nbviewer.ipython.org/github/ip…
Mastering Markdown: https://guides.github.com/features/ma…
Codecademy’s Python course: http://www.codecademy.com/en/tracks/p…
DataQuest: https://dataquest.io/missions
Google’s Python class: https://developers.google.com/edu/pyt…
Python for Informatics: http://www.pythonlearn.com/

== SUBSCRIBE! ==
https://www.youtube.com/user/datascho…

== LET’S CONNECT! ==
Blog: http://www.dataschool.io
Newsletter: http://www.dataschool.io/subscribe/
Twitter: https://twitter.com/justmarkham
GitHub: https://github.com/justmarkham

python lesson iris

Now that we’ve set up Python for machine learning, let’s get started by loading an example dataset into scikit-learn! We’ll explore the famous « iris » dataset, learn some important machine learning terminology, and discuss the four key requirements for working with data in scikit-learn.

This is the third video in the series: « Introduction to machine learning with scikit-learn ». Read more about the video here:
http://blog.kaggle.com/2015/04/22/sci…

The IPython notebook shown in the video is available on GitHub:
https://github.com/justmarkham/scikit…

== RESOURCES ==
Iris dataset in UCI Machine Learning Repository: http://archive.ics.uci.edu/ml/dataset…
scikit-learn dataset loading utilities: http://scikit-learn.org/stable/datasets/
Fast Numerical Computing with NumPy (slides): https://speakerdeck.com/jakevdp/losin…
Fast Numerical Computing with NumPy (video): https://www.youtube.com/watch?v=EEUXK…
Introduction to NumPy (PDF): http://www.engr.ucsb.edu/~shell/che21…

== SUBSCRIBE! ==
https://www.youtube.com/user/datascho…

== LET’S CONNECT! ==
Blog: http://www.dataschool.io
Newsletter: http://www.dataschool.io/subscribe/
Twitter: https://twitter.com/justmarkham
GitHub: https://github.com/justmarkham

Now that we’re familiar with the famous iris dataset, let’s actually use a classification model in scikit-learn to predict the species of an iris! We’ll learn how the K-nearest neighbors (KNN) model works, and then walk through the four steps for model training and prediction in scikit-learn. Finally, we’ll see how easy it is to try out a different classification model, namely logistic regression.

This is the fourth video in the series: « Introduction to machine learning with scikit-learn ». Read more about the video here:
http://blog.kaggle.com/2015/04/30/sci…

The IPython notebook shown in the video is available on GitHub:
https://github.com/justmarkham/scikit…

== RESOURCES ==

Iris dataset in UCI Machine Learning Repository: http://archive.ics.uci.edu/ml/dataset…
Nearest Neighbors user guide: http://scikit-learn.org/stable/module…
KNeighborsClassifier class documentation: http://scikit-learn.org/stable/module…
Logistic Regression user guide: http://scikit-learn.org/stable/module…
LogisticRegression class documentation: http://scikit-learn.org/stable/module…
Videos from An Introduction to Statistical Learning: http://www.dataschool.io/15-hours-of-…

== SUBSCRIBE! ==
https://www.youtube.com/user/datascho…

== LET’S CONNECT! ==
Blog: http://www.dataschool.io
Newsletter: http://www.dataschool.io/subscribe/
Twitter: https://twitter.com/justmarkham
GitHub: https://github.com/justmarkham

Catégorie

oct

OpenLdap

Posted by : admin | On : 24 octobre 2011

Category: Informatique, Système

Tags:Apache directory Studio, Debian, LDAP, Linux, OpenLDAP, Python

http://blog.thelinuxfr.org/Installation-et-configuration-d-un.html

http://www.debian-administration.org/article/OpenLDAP_installation_on_Debian

Open LDAP

Installation des packages

sudo apt-get install slapd ldap-utils  libdb4.6
 sudo dpkg-reconfigure slapd
 root@artaud:~# /etc/init.d/slapd restart

Remplir notre ldap

sudo slapadd  -v -l ~/init.ldif
 ou ldapadd -c -x -D cn=admin,dc=spinlock,dc=hr -W -f ~/init.ldif

le prompt authentification aparait

 
 dn: ou=people,dc=home
 objectClass: organizationalUnit
 ou: people

 dn: ou=groups,dc=home
 objectClass: organizationalUnit
 ou: groups

 dn: uid=lionel,ou=people,dc=home
 objectClass: inetOrgPerson
 objectClass: posixAccount
 objectClass: shadowAccount
 uid: lionel
 sn: Porcheron
 givenName: Lionel
 cn: Lionel Porcheron
 displayName: Lionel Porcheron
 uidNumber: 1000
 gidNumber: 10000
 gecos: Lionel Porcheron
 loginShell: /bin/bash
 homeDirectory: /home/lionel
 shadowExpire: -1
 shadowFlag: 0
 shadowWarning: 7
 shadowMin: 8
 shadowMax: 999999
 shadowLastChange: 10877
 mail: lionel.porcheron@home.com
 postalCode: 31000
 l: Toulouse
 o: home
 mobile: +33 (0)6 xx xx xx xx
 homePhone: +33 (0)5 xx xx xx xx
 title: System Administrator
 postalAddress:
 initials: LP

Vérifier le peuplement de son LDAP

sudo slapcat
 ldapsearch -x
sortie écran

# extended LDIF
 #
 # LDAPv3
 # base <> (default) with scope subtree
 # filter: (objectclass=*)
 # requesting: ALL
 #

 # search result
 search: 2
 result: 32 No such object

 # numResponses: 1
 root@artaud:~# ldapsearch -x
 # extended LDIF
 #
 # LDAPv3
 # base <> (default) with scope subtree
 # filter: (objectclass=*)
 # requesting: ALL
 #

 # search result
 search: 2
 result: 32 No such object

 # numResponses: 1

Configuration de /etc/ldap/ldap.conf

URI ldap://127.0.0.1/

 
 database    bdb

 suffix          "dc=admin,dc=home"

 #rootdn          "cn=Manager,dc=example,dc=com"
 rootdn          "cn=admin,dc=admin,dc=home"
 # Cleartext passwords, especially for the rootdn, should

 # be avoided.  See slappasswd(8) and slapd.conf(5) for details.
 # Use of strong authentication encouraged.

 #rootpw            {SSHA}rpns/vNaQ1h8qxzNGdnuS+mJtHGuzv+k
 {SSHA}4+B3Cqnpzf454dzgREe0FBsIQ19Y8Trp

 # rootpw          {crypt}ijFYNcSNctBYg

 root@artaud:~# sudo slapadd  -v -l ~/init.ldif

Annexe :

init.ldif

dn: ou=people,dc=home
 objectClass: organizationalUnit
 ou: people
 dn: ou=groups,dc=home
 objectClass: organizationalUnit
 ou: groups
 dn: uid=lionel,ou=people,dc=home
 objectClass: inetOrgPerson
 objectClass: posixAccount
 objectClass: shadowAccount
 uid: lionel
 sn: Porcheron
 givenName: Lionel
 cn: Lionel Porcheron
 displayName: Lionel Porcheron
 uidNumber: 1000
 gidNumber: 10000
 gecos: Lionel Porcheron
 loginShell: /bin/bash
 homeDirectory: /home/lionel
 shadowExpire: -1
 shadowFlag: 0
 shadowWarning: 7
 shadowMin: 8
 shadowMax: 999999
 shadowLastChange: 10877
 mail: lionel.porcheron@home.com
 postalCode: 31000
 l: Toulouse
 o: home
 mobile: +33 (0)6 xx xx xx xx
 homePhone: +33 (0)5 xx xx xx xx
 title: System Administrator
 postalAddress:
 initials: LP

Installer un client LDAP

Apache Directory Studio Certaines le meilleur client Rcp que je connaisse concernant l’utilisation quotidienne de OPENLDAP http://directory.apache.org/studio/

les plus connu Gq et Luma
apt-get install luma
puis telecharger les sources sur le site de Luma . Version testé v2.4

Exécutez

python install –prefix=/usr/share
 /usr/share == PATH default

Java generalities

Grand collisionneur de hadrons (LHC)

Jar Executable

Samba

JMS Java

python datascience startup

python lesson iris

Catégorie

OpenLdap

Installation des packages

Remplir notre ldap

Vérifier le peuplement de son LDAP

sortie écran

Configuration de /etc/ldap/ldap.conf

Annexe :

Installer un client LDAP

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