The November edition of the TechLunch will be about Machine Learning. What it is, what it isn't and what you can do with it.
We will have three talks of 15mn each (with a 5mn break for questions in between), followed by a more casual networking time.
Machine Learning is becoming such a buzzword that it seems everybody is doing it in some way or another (sometimes along with some Big Data, Reactive Programming and a bit of Artificial Intelligence).
In this event we'll see what it really is about, what people already use it for and how you can use it too.
Machine Learning for Busy People by Fabien Vauchelles
Random Forest, Cross Validation, Clustering... This is the new language of the developer! When we look closer, Machine Learning is simple: we clean data, we assemble datasets and we evaluate algorithms. It's a lot of experiments. I'll introduce you to this universe by the example.
What machine learning can do with unstructured data: text and images by Charles Ollion
Recent advances in Machine Learning, known as Deep Learning, enables to harness complex data such as natural language or pictures. I'll introduce the new perspectives offered by these new technologies, easy ways to try it yourself, along with some very impressive examples
Machine Learning in practice : finding people names in full-text by Remi Mélisson
As an actual case, we'll describe Named Entity Recognition (https://en.wikipedia.org/wiki/Named-entity_recognition) and how we can tackle it with the help of a Machine Learning approach.Using it as toy problem, we can isolate and describe the different steps towards model training.
Note that this event is scheduled during lunch. We will have food for all the registered persons, but try not to be late.
Our elevator is fixed \o/. Entrance will be at the corner of Rue St-Martin and Rue Pernelle, 4th floor.
Talks will be in English, recorded and published on YouTube afterwards.