Answer:
The lossy compression method is also known as irreversible compression and is beneficial if the quality of the data is not your priority. It slightly degrades the quality of the file or data but is convenient when one wants to send or store the data. This type of data compression is used for organic data like audio signals and images. The algorithm use in Lossy compression include: Transform coding, DCT, DWT, fractal compression, RSSMS.
The Lossless compression method is also known as reversible compression and is capable of reconstituting the original form of the data. The quality of the data is not compromised. This technique allows a file to restore its original form. Lossless compression can be applied to any file format can improve the performance of the compression ratio. The algorithm use in Lossless compression include: RLW, LZW, Arithmetic encoding, Huffman encoding, Shannon Fano coding.
Advantage of Lossy compression: Lossy compression can achieve a high level of data compression when compared to lossless compression.
Advantage of Lossless compression: Lossless compression doesn’t degrade the quality of data during compression
Disadvantage of Lossy compression: Lossy compression degrades the quality of the data during compression
Disadvantage of Lossless compression: Lossless compression has less data holding capacity when compared to lossy method
Example of type of data for Lossless compression: Text
Example of type of data for Lossy compression: Audio
Explanation:
<span>The Standard and Datacenter editions.</span>
Explanation:
SELECT
distributor_id,
COUNT(*) AS TOTAL,
COUNT(IF(level='exec',1,null)),
COUNT(IF(level='personal',1,null))
FROM sometable;
In the NumPy function, the data preparation technique that is used to help machine learning algorithms is called the reshape technique or function
For better understanding, let us explain what the reshape function means
- The numpy package helps to give the right tools for scientific and mathematical computations in python
. it includes functions that cam be used to perform common linear algebra operations, fast Fourier transforms, and statistics
The reshape function simply alter or change the row and column arrangement of data in numpy function and it is said to just give new shape to an array without the altering of its data.
from the above, we can therefore say that the answer In the NumPy function, the data preparation technique that is used to help machine learning algorithms is called the reshape technique or function is correct
learn more about reshape function from:
brainly.com/question/24728884
Answer:
The answer to this question is given below in the explanation section.
Explanation:
The value stored by a variable can be changed after it is assigned(true).
The value of a variable can be changed after it is assigned, for example:
int a=10;
and we can change the value of variable a in letter program such as:
a=15;
Variables are a name for a spot in the computer's memory (true).
it is true, because the variables value stored in the computer's memory and we can access theses values by their name (variable name). so Variables are a name for a spot in the computer's memory.
Variable names can be words: such as temperature or height (true).
Yes, the variable name can be words such as height, width, temperature etc.
The value stored by a variable cannot be changed after it is assigned (false).
It is noted that the value stored by a variable can be changed after it is assigned. However, it is noted that is some programming language, you can't change the value of static variable.
