5 ways how AI can improve your demand forecasting
Download the guide and learn how deepsense.ai can leverage the accuracy of your organization’s demand forecasting.
This author has yet to write their bio.Meanwhile lets just say that we are proud deepsense.ai contributed a whooping 39 entries.
Download the guide and learn how deepsense.ai can leverage the accuracy of your organization’s demand forecasting.
Computer vision is a foundational element of smart factory solutions. At deepsense.ai we have created diverse AI-driven, automated computer vision-based solutions that undertake the most demanding challenges in many different production lines.
The concept of machine learning is derived from advanced data analysis of pattern and dependency recognition. ML assumes that when models analyze new data, they can adapt independently and use this new knowledge to develop by learning from previous experiences. Machine learning models can enhance nearly every aspect of a business, from marketing and sales to maintenance.
Interview with Michał Iwanowski, VP of Engineering, about AI development in 2021.
Cost of risk is one of the biggest components in banks’ cost structure. Thus, even a slight improvement in credit risk modelling can translate in huge savings. That’s why machine learning is often implemented in this area.
deepsense.ai is pleased to announce that its Management Board has welcomed Michał Iwanowski as a new Board Member.
deepsense.ai has been selected to be a part of Silicon Valley Innovation Platform run by the Plug and Play Tech Center, the world’s largest early stage investor, accelerator, and corporate innovation hub.
Tomasz Kułakowski, CEO, talks about how deepsense.ai entered the new decade and dealt with the new business reality.
It is the second time deepsense.ai researchers have presented at the NeurIPS conference. In the most recent installment of the world’s most closely watched AI conference, Piotr Miłoś described CRTS research during the Machine Learning for Autonomous Driving workshop.
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