“Arvostus kantautuu arkeen” – Mikael Saviaro nauttii myynnin arvostuksesta Talenomilla

Mikael Saviaro työskenteli ennen Talenomille tuloa pankki- ja vakuutusalalla yhdeksän vuoden ajan. Rooleja Saviaro ehti kerätä vyölleen monenlaisia; hän toimi mm. puhelinpalvelussa asiakasneuvojana, kouluttajana, myyntivalmentajana ja tiimipäällikkönä....

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AI at Talenom: Explainable AI

Machine learning models learn dependencies between inputs and labels from the training set during training. However, dependency does not always imply the causality that we really want to learn. This becomes a problem when the data distribution of production...

AI at Talenom: Active Learning

One of the most common use-case of machine learning is to automate work that has been previously done manually. The learning is typically based on training data where a decision (output) is made based on a set of conditions (inputs). After training...

AI at Talenom: Partial Label Learning

In machine learning jargon, supervised learning means that we have a correct label for every training example in the training set. The opposite setting for supervised learning is unsupervised learning in which we have a set of inputs without the desired...

AI at Talenom

This blog is an introduction to our new blog series. The blog series covers some interesting topics that we have faced during developing of productionized AI system. The AI system we are covering in the blog series is automatic posting of purchase...