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data science project

How to Succeed in Data Science Projects

by Lukáš Dvořák, Business Development Manager

The effectiveness of data science projects is one of the hottest topics in business intelligence nowadays. On the one hand, we are discussing the huge potential of artificial intelligence in executing sophisticated tasks for businesses. On the other hand, we see the harsh reality of today. Large companies like banking institutions are struggling hard to…

artificial intelligence for banking

Building a Data Science and Analytics Competence in Banking

by Barbora Fuksa, Business Development Manager

In the last five years of providing data science as a service to Europe’s largest banks, we have faced plenty of cases where banks were unprepared to work with their data. Unfortunately, this problem arises not only at the stage of creating a competency in the field of data science and…

Bayesian networks modelling

Bayesian Networks: From zero to working model

by Dominik Matula, Data Scientist

Over the years, we have often heard from our clients that black box machine learning solutions are unacceptable. In the previous article, we went over three key questions to ask before using a black box model, and we proposed Bayesian networks as…

the alternative solution to a black box

Machine Learning Without Black Boxes

by Dominik Matula, Data Scientist

With the boost of computing power in past years, it has happened that almost anyone can run a sophisticated machine learning model, e.g. neural networks. And with modern frameworks such as Tensorflow, it is quite accessible and also popular to do everything with such a cool tool. But over the years, we have often heard…

artificial intelligence for customer segmentation in banking

Customer Segmentation in Banking

by Lukáš Dvořák, Business Development Manager

Every company doing business in retail has been dealing with customer segmentation, and so have banking organizations trying to describe their client base effectively. Customer segmentation is key to the success of marketing campaigns, product cross-selling and risk scoring. That’s why it’s critical for financial institutions to set up an efficient customer segmentation strategy.