Are you a master at the art of feature engineering yet?

Are you interested in getting more insights and in learning more about the creative process of characterising data in terms of features that can help you reach better results when you are applying a data mining or machine learning algorithm? This is your chance then, as Sirris will be organising a second edition of this training session.

After the great success of the first edition, we decided to organise a new session on 22 June.

Feature engineering is the process of extracting and selecting relevant, informative and distinguishing characteristics from your data, which can subsequently be used as input for a machine learning algorithm. As the quality of your features largely influences the quality of the results, feature engineering is one of the keys to success in successfully applying machine learning. While it is typically a creative and work-intensive process, understanding the methodology, tricks of the trade and common pitfalls can help you go a long way.

You can read further on the art of feature engineering in the following blogpost.

Register for our next training session dedicated to feature engineering in Zwijnaarde on 22 June. In this session, we will discuss in detail the methodology behind it, including various methods for feature construction, selection, normalisation, etc.