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The Mac vs PC debate did not start in the recent past; it was present as long as I can remember, and both the parties have their points of upsides and downsides, but coming to security, which one is more resistant to cyber threats? Let us find out.Cybercriminals are ever-evolving; the cyber threats initially to Macs were far less than those to PC, but hackers always come up with a way to do their job and, recently, even with Mac. Macs are getting quite vulnerable, just like PC.While Macs' elegant look and simplicity contribute to their popularity, the lack of ... Read More
To find the matrix product of two arrays, use the numpy.matmul() method in Python Numpy. If both arguments are 2-D they are multiplied like conventional matrices. Returns the matrix product of the inputs. This is a scalar only when both x1, x2 are 1-d vectors.The out is a location into which the result is stored. If provided, it must have a shape that matches the signature (n, k), (k, m)->(n, m). If not provided or None, a freshly-allocated array is returned.StepsAt first, import the required library −import numpy as npCreate two 2D arrays −arr1 = np.array([[5, 7], [10, 15]]) arr2 ... Read More
Malicious software, or malware, is any software that causes damage to a computer system. Malware can take the shape of worms, viruses, trojans, spyware, adware, and rootkits, among other things, and can steal confidential information, erase documents, or install software that has not been allowed by the user.How Does Malware Get Past Security Software?Malware takes advantage of security flaws (bugs or vulnerabilities) in the operating system's design and applications (such as older versions of Microsoft Internet Explorer supported by Windows XP) and susceptible versions of browser plugins. Even installing new versions of such plugins does not always result in the ... Read More
To subtract arguments element-wise with different shapes, use the numpy.subtract() method in Python Numpy. The out is a location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.The condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an ... Read More
To multiply arguments element-wise with different shapes, use the numpy.multiply() method in Python Numpy.The out is a location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.The condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized ... Read More
To add arguments element-wise with different shapes, use the numpy.add() method in Python Numpy. The out is a location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.The condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an ... Read More
To subtract arguments element-wise, use the numpy.subtract() method in Python Numpy. The output is set "float" using the "dtype" parameter.The out is a location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.The condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original ... Read More
To subtract arguments element-wise, use the numpy.subtract() method in Python Numpy. The out is a location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.The condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array ... Read More
To add arguments element-wise, use the numpy.add() method in Python Numpy. The output is set "float" using the "dtype" parameter.The out is a location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.The condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original ... Read More
To return the fractional and integral parts of array values, use the numpy.modf() method in Python Numpy. Multiply the fractional values using the index 0 values. The fractional and integral parts are negative if the given number is negative.The out is a location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.The condition is broadcast over the input. At locations where the condition is ... Read More