Numpy (Numerical Python) for Beginners Course
#numpy #convolution
NumPy Complete Beginner Course.
NumPy (short for "Numerical Python") is a Python package that provides a powerful set of tools for working with arrays, matrices, and numerical computations. It is widely used in the scientific computing and data analysis communities because of its efficiency, flexibility, and ease of use.
At its core, NumPy provides a fast and efficient multi-dimensional array object that can be used to represent vectors, matrices, and higher-dimensional arrays. This array object is designed to support a wide range of numerical operations, including basic arithmetic operations, linear algebra, and Fourier analysis.
Content:
1. Create an Array
2. Shape and size
3. Arrange
4. Creation, Linspace
5. Zeros, Zeros Like
6. Ones Ones Like
7. Random Numbers
8. Poisson
9. Gamma Distribution
10. Beta Distribution
11. From Function
12. Save Array
13. Arithmetic Operations
14. Matrices.
One of the key benefits of using NumPy is its speed. The array object is implemented in C, which means that operations on arrays can be performed much more quickly than equivalent operations in pure Python. NumPy also includes a number of built-in functions that are optimized for speed, such as vectorized operations and functions for broadcasting arrays.
Overall, NumPy is a powerful and flexible package that provides a wide range of tools for numerical computing in Python. It is a fundamental tool for scientific computing and data analysis in Python, and is widely used in fields such as physics, engineering, and finance.
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Convolution Academy
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