Let’s travel across Asia to meet tech communities!!!

Let’s travel across Asia to meet tech communities!!!

My name is Ludwine, I am 31. After a Master’s degree in maths, I chose to learn to code to become a software engineer. In 2010, I started my first job as a Java developer, and I now work as a Data Engineer so I can combine code, math and data.

Quickly I got involved in promoting women in tech through the Duchess France association for 3 years, and now with the Ladies Of Code community.

I love traveling, and Asia has always attracted me. So I took the plunge and decided to realize one of my dreams: backpack across Asia in the next months to discover new cultures, different ways of living and thinking.

Being a technology passionate, I intend to meet tech and women communities, and learn about the local culture and the ecosystem.

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Exploring Deep Learning with LI Zhe

Exploring Deep Learning with LI Zhe

I am totally excited in this post to interview LI Zhe, a software engineer in Bordeaux, whom I have only known through email and Twitter for the past two years, and only managed to meet in real life about a month ago.

We share a common passion about Machine Learning and mathematics, and for this interview I asked her to tell us a little bit more about one of her favorite topic: Deep Learning.

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Getting started with Spark in practice

Getting started with Spark in practice

Some months ago, we, Sam Bessalah and I organized a workshop via Duchess France to introduce Apache Spark and its ecosystem.

This post aims to quickly recap basics about the Apache Spark framework and it describes exercises provided in this workshop (see the Exercises part) to get started with Spark (1.5.2), Spark streaming and dataFrame in practice.

If you want to start with Spark and come of its components, exercises of the workshop are available both in Java and Scala on this github account. You just have to clone the project and go! If you need help, take a look at the solution branch.

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Analyze accelerometer data with Apache Spark and MLlib

Analyze accelerometer data with Apache Spark and MLlib

The past months I grew some interest in Apache Spark, Machine Learning and Time Series, and I thought of playing around with it.

In this post I will explain how to predict user’s physical activity (like walking, jogging, sitting…) using Spark, the Spark-Cassandra connector and MLlib.

The entire code and data sets are available on my github account.

This post is inspired from the WISDM Lab’s study and data (not cleaned) come from here. To determine the features to use I have read this study.

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Atelier de préparation pour les Call For Papers ?

Une des raisons qui souvent nous freine pour soumettre un sujet à une conférence, c’est de trouver un sujet à présenter !

Le sujet a beaucoup été évoqué ces dernières semaines, que ce soit à Devoxx France sur la place des femmes à Devoxx ou encore lors du dernier épisode des castcodeurs : peu de femmes soumettent des sujets aux conférences.
Pas mal de CFP sont encore en cours, et certains prennent fin dans les semaines qui arrivent. Il y en a pour tous : technos Google, web, android, java…
De plus plusieurs formats d’intervention sont en général proposés : 10min, 20min, 45min, workshops…

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