One of the industries where AI has found vast application is in banking. Banks have discovered some really valuable AI use cases: fraud prevention and fraud detection, credit underwriting decisions, customer service automation via chatbots, risk management, decreasing manual workload, and so on.
The passenger number is a crucial figure in railway operations that impact the overall functioning of the commuter railway traffic. But in the case of VR Group, Finland’s government-owned railway company, with over 14 million passengers carried on long-distance rail services only in 2019, predicting passenger number requires additional helping hand by machine learning.
Iiris Lahti, former Development Director – Data Utilization at Sanoma Media Finland will introducing the learnings and best practices of how to utilize data and machine learning in designing digital media services, content, marketing and better customer experiences.
The prolific career of a data scientist can have its roots in an innocent child’s dream to predict soccer results. Or at least that was the case for Gábor Stikkel, an accomplished Senior Data Scientist at HID Global and speaker at the Data Innovation Summit 2019.
We are going to see Klarna’s story from an engineer’s and data scientist’s point of view, where first we look into their data organisation and structure, and later we’ll devote the white space to their machine learning models for superb purchase experience.
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