The term Digital Twin emerged in 2017 as one of the main technological trends according to Gartner consultancy and its results have been demonstrated in multiple areas. This article aims to introduce the concept of Digital Twin technology, reviewing some of its main benefits and presenting a practical example. In order to develop a solution to optimize its warehouse, we co-innovate in collaboration with Frit Ravich, the leading manufacturer and distributor of external brands from well-established companies such as Mars Spain, Nestlé and Ferrero (3,000 references) that serve around 50,000 points of sale every week.
Feature Engineering is a crucial step in the process of building a Machine Learning pipeline, as the features will be used by the algorithm as predictors.
Therefore, it’s advisable to prioritise building and optimizing our features to make sure that we start with a robust data model - which will result in our machine learning model achieving good results.
During the implementation of Data Science Projects, we always face cases where we have to decide on the best method of implementation in order for it to be integrated with the pipeline smoothly. The goal is to achieve the most simplistic implementation as the overall design is always complex. We focus on to simplifying our approaches as much as possible so we can keep track of all the steps and modify them easily with minimum implementation/modification time.
In today’s post, we will narrate you our journey navigating through the ocean of NULLs. This is the story of how we moved forward from the mystical, the initial expectations and assumption, to the practical, an actual problem-solving methodology that became an integral and reusable approach of our data science framework.
Machine learning has become a central topic of interest in the media, thanks to its recent successful applications in creating value in a variety of business scenarios. At Clariba, as experts in predictive analytics, we are active agents of its adoption and democratization, since we have been applying ML in our predictive solutions for a long time. When used wisely and with the proper methodology, Machine Learning techniques can offer an increase in performance to businesses and organizations of all types.