## Image Processing with NumPy

Image processing is a crucial task in scientific computing field. Generally images are stored as arrays. There are various libraries such as OpenCV, SciKit-Image and Pillow that provides powerful tools for image processing. The basic image processing tasks include image

## Linear Algebra with NumPy

Linear algebra is a field of mathematics that deals with solving systems of linear equations. Linear algebra has been widely used in geometry, functional analysis, modeling of scientific and engineering linear models. Linear algebra are usually represented using matrix and

## Working on Matrix with NumPy

Matrix is a rectangular array of items arranged in rows and columns. Matrix is one of the oldest mathematical concept that has been widely applied to different fields. Some of the major applications of Matrices are in linear transformation, solving

## Indexing, Slicing and Reshaping NumPy Arrays

In data analysis and machine learning all the data is not useful for analysis or machine learning hence we need to extract only a subset that is useful for the specified task. Indexing is a powerful technique for improving the

## NumPy Mathematical Operations

NumPy was designed to be efficient in handling numerical computations. With the power of multi-dimensonal array we can manipulate data with ease. NumPy outperforms other packages when it comes to mathematical operations as it has high performance. In this post

## NumPy Basic Operations

The long existence of NumPy in numerical computing ecosystem has made it one of the mature package for scientific computing. Many other packages have leveraged the power of NumPy for handling of multi-dimensional arrays and other numerical features. From data

## Reading And Storing Data In NumPy

NumPy has a set of methods that facilitates the reading and saving of data from text and csv files to the NumPy. At some given point you might need to work with text files or other forms of files in NumPy.

## Introduction to NumPy

NumPy is a Python library for scientific computing and data manipulation tasks. It is a powerful tool for handling multi-dimensional array objects. NumPy is used with Pandas for data analysis tasks. It comes with mathematical tools for working with linear