MEET JETTRO COENRADIE, SPEAKER AT
CODEMOTION AMSTERDAM TECH CONFERENCE

BASED IN:  Amsterdam – The Netherlands
ROLE and COMPANY: Fellow at Luminis
COMMUNITIES: Elasticsearch, 010dev, 070dev, Java, Nljug

WHY SHOULD PARTICIPANTS CHOOSE TO ATTEND YOUR TALK?
As I always tell participants of my trainings, search is all around you. The engines like Solr and Elasticsearch are easy to install and it is also not to hard to start implementing functionality. But how do you make sure you understand what the user is searching for and how do you define relevant results. After the talk you should have a better understanding of the search domain, you also will have a reasonable understanding of where to start when creating search solutions for yourself.

Title: Relevant search results (with elasticsearch)
When: Wednesday, May 17th from 11:30 to 12:10

IF YOUR TALK HAD A SOUNDTRACK, WHAT WOULD THAT BE?
While preparing for the talk I would like to take a rest with “Marian Hill – Down” moving into a bit more power with “Katatonia – Old Heart Falls” and “Nightwish – Shudder before the beautiful” and cooling down with “Gavin James – Nervous”, “Ry X- Deliverance” and wrapping up “Anneke van Giersbergen – Het Dorp”

IF YOU WERE A PARTICIPANT WHICH TALKS WOULD YOU ATTEND AND WHY?
“Fast Cars, Big Data – How Streaming Can Help Formula 1” by Tugdual Grall looks as a very interesting talk. I care about data and I am into formula 1, a good combination.

WHAT IS HAPPENING IN YOUR FIELD IN 5 YEARS?
This is of course a tough question. I am glad I sometimes know what will happen within a year. As I am working a lot in the search domain and learning fast in the Data Science track, I see a lot of parallels between the two domains. Therefore I expect more integration of the two domains. Search solutions providing Machine Learning and Data Science for things like anomaly detection but also auto classification of content. The Data Science track will become easier, as we do get more computing power we can teach the computer new tricks but I also expect the computers to start more learning themselves.