Data Analysis ... lift-off for Jupyter

Dernieres nouvelles ...

Last minute details ... I've been asked to give the talk in English, I think that is OK with most/all people.

Please

• communicate your full name to me if you haven't already done so

• bring your ID to show to the security guard or you won't be allowed in

When you arrive you will have to pass by the "Poste de Garde" at the bottom of the image below.

For those coming by car, you can proceed directly to the B10 as indicated.

For those walking I'll wait until about 19h05 at the Accueil (close to the "Poste de Garde") and we will walk to the B10 together.

If you arrive late then please make your own way to B10, and call on arrival

(I'll send my mobile number by mail and give my phone to a colleague)

http://photos3.meetupstatic.com/photos/event/7/7/e/7/600_442290695.jpeg

Changement de lieu, vu le nombre d'inscrits j'ai decide de faire ca chez HP. Le but etant de pouvoir accueillir plus de monde en esperant que ca ne pose pas de probleme de transport.

HP est accessible en TRAM ligne A, etant a 500m de l'arret Pole-Sud/Alepexpo,

Voici l'access a HP sur Google Maps: http://bit.ly/1JdNsvd

Je vous propose de se retrouver a l'accueil HP a 19h et de la en marchera jusqu'au solution center. Eventuelles retardataires peuvent nous rejoindre directement au B10 (je fournira un plan du site).

NOTE: Je propose qu'on termine le Meetup a 21h15. Il faudrait que quelqu'un avec badge HP puisse vous amene a la sortie.

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Enfin on aura notre Meetup sur Jupyter ... ca tombe bien,

la version IPython 4.0 / Jupyter 4.0 viend de sortir !!

Du coup je vais vous presenter ce que j'ai propose pour MixIT cette annee.

Bien que le talk etait accepte par MixIT j'ai du annuler a cause d'une deplacement professionel.

Par contre je suis a la recherche d'eventuel co-speaker/volontaire pour re-proposer ca en talk et lab l'annee prochaine a MixIT.

Voici l'abstract tel que je l'avais soumis a MixIT:

This talk is aimed at those beginners interested to learn about Data Analysis (not necessarily BigData) and in particular the tools available and their evolution.

I will demonstrate some capabilities of the Jupyter project (so as not to have a Python bias) alongside IPython itself, and RStudio commonly used in Scientific Data Analysis.

Where possible the talk will be a plagiarism of existing exercises based on real world data from recent books or MOOCs on the subject - because there are many excellent sources on the subject !!

The intention is to present a non-exhaustive language-agnostic view of some tools available and their usage. I hope for example that people seeing the capabilities of the Python module sympy run from Jupyter performing symbolic processing to solve equations, whilst presenting its' results as one would write such formulas (Latex rendered via MathJAX.js) will have the same wow effect as it had on me.

We will see several visualization libraries so at the very least people will have seen some pretty graphs, images ... maybe even seen some music via a piano keyboard rendered in the browser.

My intention is to show examples and provide a Dockerfile, github repo to allow attendees to perform the exercises themselves. If popular I hope to present a lab on this subject next year.

Ideas for now

Wow, I didn't know such tools were available - I want to play with this stuff, I want to contribute !