Pitfalls of ML at (not only) Kiwi.com – Roman Rožnik

  Machine learning

No doubt machine learning is a hot topic in recent years, it seem's everybody can easily become a data scientist and do ML within few lines of code. Reality is much harder. Understanding the problem, preparing right training data, cleaning them, designing features, interpretability/complexity of the model, defining right metrics, looking at false positives/negatives, interpretation of ML results or AB tests - those are topics highly tied with data science that are often overlooked and underrated. I'd like to emphasize that those are very important and ML itself is just one small piece of complex data science puzzle. Bringing data science and ML approaches to the crazy company like Kiwi.com is very hard and often frustrating costs lot of blood, toil, tears and sweat and brings disillusion, sadness and lot of fails.

Roman has always been the developer most interested in math and algorithms. With a stroke of luck, he became the machine learning guy at Seznam.cz where he introduced ML to the full-text search team. After he fulfilled his mission with Seznam.cz, he decided to bring the ML and data science approach to Kiwi.com.

Language: English

- Talk
- Discussion
- Networking (ImpactHub)

Machine Learning Meetups (MLMU) is an independent platform for people interested in Machine Learning, Information Retrieval, Natural Language Processing, Computer Vision, Pattern Recognition, Data Journalism, Artificial Intelligence, Agent Systems and all the related topics. MLMU is a regular community meeting usually consisting of a talk, a discussion and a subsequent networking. At the end of the year 2016, MLMU spread also to Brno and Bratislava.