This repository will be used as code and instructions source for the HACKATHON DANONE AI MASTERS OPOLE 2019.
A pre-hackathon Meetup, IT Meetup Opole#2, is organised on March 21st, 2019. All the information shared during this event is posted here containing some basic instructions on how the data was prepared and a full description of the industrial processes followed during the baby-food production
The data explained here represents the historical data from several years of baby-food production. Different recipes are under consideration. This data is being released as a challenge for the HACKATHON DANONE AI MASTERS OPOLE 2019, MACHINE LEARNING CHALLENGE.
As part of the digitalisation efforts and implementation of I4.0 best practices, Danone Opole starts its data-journey by preparing historical data comprising the orders, characteristics of the raw materials used on each recipe, variables used during the food-processing and different variables measured from the semi-finished product.
The challenge, if you decide to accept it! is to build a model that will allow estimating the food-processing parameters that will provide the expected parameters in the semi-finished products
Mentoring during the events
I have been tasked to support the Danone Opole team in the preparation of the data and further mentoring during the events.
To introduce the participants to the Hackathon's challenge, I am sharing the process of preparing the data from the existing sources to a more useful format. Extraordinary efforts were made to create a robust data model and remove, as much as possible, inconsistencies and errors introduced during the digitisation of the paper-based data and further match to available digital data sources.
If you would like to get in touch please visit my LinkedIn profile