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Details for:
Bisht K. NumPy. From Basic to Advance for Machine Learning 2022
bisht k numpy from basic advance machine learning 2022
Type:
E-books
Files:
1
Size:
17.3 MB
Uploaded On:
Nov. 12, 2022, 8:44 a.m.
Added By:
andryold1
Seeders:
5
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0
Info Hash:
4EA41472B53DFBBB32850B5DE57D0384095DDEE8
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Textbook in PDF format NumPy, which stands for Numerical Python, is a library consisting of multidimensional array objects and a collection of routines for processing those arrays. Using NumPy, mathematical and logical operations on arrays can be performed. NumPy is a Python package. It stands for ‘Numerical Python’. It is a library consisting of multidimensional array objects and a collection of routines for processing of array. It also has functions for working in domain of linear algebra, fourier transform, and matrices. Using NumPy, a developer can perform the following operations - Mathematical and logical operations on arrays. - Fourier transforms and routines for shape manipulation. - Operations related to linear algebra. NumPy has in-built functions for linear algebra and random number generation. NumPy is often used along with packages like SciPy (Scientific Python) and Matplotlib (plotting library). This combination is widely used as a replacement for MatLab, a popular platform for technical computing. However, Python alternative to MatLab is now seen as a more modern and complete programming language. It is open-source, which is an added advantage of NumPy. The most important object defined in NumPy is an N-dimensional array type called ndarray. It describes the collection of items of the same type. Items in the collection can be accessed using a zero-based index. Every item in a ndarray takes the same size as the block in the memory. Each element in ndarray is an object of the data-type object (called dtype). Any item extracted from ndarray object (by slicing) is represented by a Python object of one of array scalar types. Why Use NumPy? In Python we have lists that serve the purpose of arrays, but they are slow to process. NumPy aims to provide an array object that is up to 50x faster than traditional Python lists. The array object in NumPy is called ndarray, it provides a lot of supporting functions that make working with ndarray very easy. Arrays are very frequently used in Data Science, where speed and resources are very important. Data Science: is a branch of Computer Science where we study how to store, use and analyze data for deriving information from it
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Bisht K. NumPy. From Basic to Advance for Machine Learning 2022.pdf
17.3 MB
