Data representation in bits in machine learning

What are representations in machine learning?
Representation Learning is a process in machine learning where algorithms extract meaningful patterns from raw data to create representations that are easier to understand and process.
These representations can be designed for interpretability, reveal hidden features, or be used for transfer learning..
What is the data representation in bits?
The 0s and 1s used to represent digital data are referred to as binary digits — from this term we get the word bit that stands for binary digit.
A bit is a 0 or 1 used in the digital representation of data..
What types of data can be represented in binary?
All forms of data can be represented in binary system format.
Other reasons for the use of binary are that digital devices are more reliable, small and use less energy as compared to analog devices..

Sep 15, 2019In implementing most of the machine learning algorithms, we represent each data point with a feature vector as the input.

Can number formats reduce the cost of machine learning?

In this lecture, we’ll talk about the relatively recent trend of using number formats with a small number ofbits to reduce the computational cost of machine learning training

But ﬁrst, we need to understand thebaseline: what do traditional machine learning applications do?

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Data representation in bits in machine learning

What are representations in machine learning?

What is the data representation in bits?

What types of data can be represented in binary?

Can number formats reduce the cost of machine learning?