There are 4 repositories under numpy-matrix topic.
Numpy is a general-purpose array-processing package. It provides a high-performance multidimensional array object and tools for working with these arrays. It is the fundamental package for scientific computing with Python. Besides its obvious scientific uses, Numpy can also be used as an efficient multi-dimensional container of generic data.
It includes the basic and advance numpy array manipulations. The topics like indexing, slicing, fast element array-wise functions, mathematical and statistical methods, filing, linear algebra functions, pseudo-random numbers, reshaping, splitting, concatenating,tiles, repeating, where( ) function & numpy advanced array manipulation are implemented.
NumPy is the fundamental package for scientific computing with Python. It contains among other things: a powerful N-dimensional array object sophisticated (broadcasting) functions tools for integrating C/C++ and Fortran code useful linear algebra, Fourier transform, and random number capabilities
This module gets first trained by the pre-trained haar-cascade classifier, then using collected face data, it recognizes the user.
basic machine learning code
A utility application that simplifies texture manipulation. Using Numpy and PIL
The fundamentals of Python NumPy Library.
NumPy (short for Numerical Python) is a powerful Python library used for working with arrays, matrices, and numerical computations.
Решение инженерных и экономических задач с NumPy
I want make this course, because I want to learning how to use the Python programming language for Computer Vision.
A repository to store sample python programs with NumPy library to learn how numpy working with Arrays
Some stuff i keep going back to while doing Data Schinece projects, that i've used for practicing
Numpy_Basics
Code to create a Pairwise Zip code Distance Matrix and use an index lookup. This is a tiny utility I built, for use in my work, but I figured it might be helpful to anyone else dealing with zip/postal code distances
Data analysis and python programming
A machine learning model after detailed image processing applications that classifies a bee as either honey bee or bumble bee
A short numpy tutorial for quick reference
Sudoku originally called Number Place is a logic-based, combinatorial number-placement puzzle. The objective is to fill a 9×9 grid with digits so that each column, each row, and each of the nine 3×3 subgrids that compose the grid (also called "boxes", "blocks", or "regions") contain all of the digits from 1 to 9. The puzzle setter provides a partially completed grid, which for a well-posed puzzle has a single solution. Completed games are always an example of a Latin square which include an additional constraint on the contents of individual regions. For example, the same single integer may not appear twice in the same row, column, or any of the nine 3×3 subregions of the 9×9 playing board. French newspapers featured variations of the Sudoku puzzles in the 19th century, and the puzzle has appeared since 1979 in puzzle books under the name Number Place.However, the modern Sudoku only began to gain widespread popularity in 1986 when it was published by the Japanese puzzle company Nikoli under the name Sudoku, meaning "single number".It first appeared in a U.S. newspaper, and then The Times (London), in 2004, thanks to the efforts of Wayne Gould, who devised a computer program to rapidly produce unique puzzles.
Numerical Python, working with numerical data in Python, going from Python lists to Numpy arrays, CSV data files using Numpy, and etc..
In-depth exploration of essential NumPy functions
Python Numpy Examples