010Dasha010
14.05.2023 22:50

надо написать транскрипцию надо​

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Ответ:
Ataka4
13.01.2023 15:41
She teaches English in our school
She doesn't teach English in our school
Does she teach English in our school
She is teaching us to swim now
Is she teaching us to swim?
She isn't teaching us to swim
She will teach him to speak Spanish next year
Will she teach him Spanish?
She won't teach him Spanish
He has breakfast at 8 o'clock every morning
Does he have breakfast at 8?
He doesn't have breakfast at 8
He is having breakfast now
Is he having breakfast?
He isn't having breakfast
He will have breakfast at 9 o'clock tomorrow
Will he have breakfast?
He won't have breakfast
They do homework every day
Do they do homework?
They don't do homework
They are doing homework now
Are they doing homework?
They aren't doing homework
They will do homework in the evening
Will they do homework in the evening?
They won't do homework in the evening
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Ответ:
kceniaart18
02.04.2022 05:19

The article is devoted to the innovative technology for data visualisation.

The article deals with the use of VR to deliver data visualisation in a virtual environment.

The article touches upon the issues of current setbacks to find an application that can combine Artificial Intelligence, Big Data and Virtual/Augmented Reality.

The article is about the platform which uses smart mapping, smart routines, machine learning and natural language processing to identify important patterns and display them in the virtual environment, which can then be customised by users. The platform can be applied to any industry that relies on data analytics, and lets users examine up to 10 dimensions of data.

The purpose of the article is to introduce the audience to the Merging Virtual Reality and Big Data systems.

Much attention is given to the adaptive and disruptive features of existing VR applications.

It is reported that the human brain can only process so much data before it becomes meaningless. However, through analysing the reactions of users within the experience, graphics can be altered in real time to maximise understanding.

It is spoken in detail about the fact the machine learning alone is faster and more efficient than traditional techniques. Pairing VR with data visualisation is also an enabler for new business models, which combine the expertise of co-workers in different geographic locations. However, in light of upcoming legislation on data sharing and analysis, businesses will need to be careful with the machine learning platforms they use.

The article gives a detailed analysis of practical applications of such powerful data processing systems for businesses and the likely negative outcomes.

The following conclusions are drawn: understanding and sharing comprehensive data is great, but analysing the wrong data (including private or sensitive) could be damaging to a business or even the whole industry.  

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