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In the big data era, the need for fast robust machine learning techniques is rapidly increasing.
In the big data era, with the ever increasing complexity of machine learning models such as deep learning, the demand for large amounts of labeled data is growing at an unprecedented scale.
The big data era has a high impact on forensic data analysis.
Especially, they become more and more relevant in the big data era.
Communication between information processing systems becomes a challenge, especially in the "big data" era.
Stratos designs big data systems which are tailored for the new challenges posed by the big data era, i.e., systems that (a) are adaptive and easy to use by non experts, requiring minimum tuning and set-up effort and (b) can cope with the ever increasing rates of incoming data and the ever increasing demands for fast reactions to data searches.
The entity reconciliation (ER) problem aroused much interest as a research topic in today's Big Data era, full of big and open heterogeneous data sources.
The academic and industry have entered big data era in many computer software and embedded system related fields.
For that, this unprecedented smart grid data require an effective platform that takes the smart grid a step forward in the big data era.
In big data era, social networks, such as Twitter, Weibo, Facebook, are becoming more and more popular worldwide.
This is a normal trilogy in the big data era.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com