O'Reilly Media - Data
JULY 18, 2018
In the early phases of adopting machine learning (ML), companies focus on making sure they have sufficient amount of labeled (training) data for the applications they want to tackle. In light of recent headlines ( Facebook and Cambridge Analytica ), the general public is much more aware of data collection, storage, and sharing.
Altexsoft
NOVEMBER 17, 2021
As today’s digital storages can serve large amounts of items, it becomes difficult to categorize them manually. So businesses employ machine learning (ML) and Artificial Intelligence (AI) technologies for classification tasks. Namely, we’ll look at how rule-based systems and machine learning models work in this context.
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TechCrunch
OCTOBER 7, 2021
The underlying large-scale metrics storage technology they built was eventually open sourced as M3. Mao and co-founder Rob Skillington (CTO) founded Chronosphere on the back of early work that they started at Uber, where they built an observability platform very specific to Uber’s needs as a business.
The Agile Monkey
MARCH 14, 2023
Event-driven machine learning will enable a new generation of businesses that will be able to make incredibly thoughtful decisions faster than ever, but is your data ready to take advantage of it? Why making the extra investment on development time and data storage? This constant stream of events provides extra benefits.
d2iq
FEBRUARY 22, 2021
Do you really have the skills and time to create custom components to wire these up, make them work and scale at your organization, and of course maintain the base technologies and the glue code that makes up 95% of a machine learning platform, with documentation that does not introduce bus factors of one everywhere?
Zayo
JANUARY 29, 2020
Many experts believe that the speed and low latency of 5G will enhance the capability of other technologies, including AI, machine learning and robotics. For some time now, the industry has been talking about edge approaches that bring compute, networking and storage closer to the point that data is generated.
Altexsoft
JANUARY 27, 2022
As of today, different machine learning (and specifically deep learning) techniques capable of processing huge amounts of both historic and real-time data are used to forecast traffic flow, density, and speed. They are usually easier, faster, and cheaper to implement than machine learning ones.
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