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https://github.com/mohd-faizy/learn_numpy
NumPy (short for Numerical Python) is a powerful Python library used for working with arrays, matrices, and numerical computations.
https://github.com/mohd-faizy/learn_numpy
array-manipulations numpy numpy-arrays numpy-matrix numpy-neural-network numpy-python numpy-tutorial
Last synced: 28 days ago
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NumPy (short for Numerical Python) is a powerful Python library used for working with arrays, matrices, and numerical computations.
- Host: GitHub
- URL: https://github.com/mohd-faizy/learn_numpy
- Owner: mohd-faizy
- Created: 2021-03-02T15:07:41.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2024-06-29T13:52:47.000Z (4 months ago)
- Last Synced: 2024-06-30T00:17:52.578Z (4 months ago)
- Topics: array-manipulations, numpy, numpy-arrays, numpy-matrix, numpy-neural-network, numpy-python, numpy-tutorial
- Language: Jupyter Notebook
- Homepage:
- Size: 1.02 MB
- Stars: 1
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
[](https://github.com/mohd-faizy)
[](https://github.com/mohd-faizy/Learn_Numpy)
# Numpy
Welcome to the Numpy repository! This repo is dedicated to providing helpful resources, tutorials, and examples for using the Numpy library in Python.
## Table of Contents
- [Numpy](#numpy)
- [Table of Contents](#table-of-contents)
- [Roadmap](#roadmap)
- [Introduction](#introduction)
- [Installation](#installation)
- [Usage](#usage)
- [Creating an Array](#creating-an-array)
- [Basic Operations](#basic-operations)
- [Advanced Operations](#advanced-operations)
- [Features](#features)
## Roadmap
## Introduction
Numpy is a powerful and flexible open-source library for numerical computing in Python. It provides support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays.
This repository aims to help users of all skill levels to better understand and utilize the Numpy library through comprehensive guides, code snippets, and example projects.
## Installation
To install Numpy, you can use pip, the Python package installer. Ensure you have Python installed, then run:
```bash
pip install numpy
```
For more detailed installation instructions, please refer to the [official Numpy installation guide](https://numpy.org/install/).
## Usage
Here are some basic examples to get you started with Numpy:
### Creating an Array
```python
import numpy as np
array = np.array([1, 2, 3, 4, 5])
print(array)
```
### Basic Operations
```python
import numpy as np
array = np.array([1, 2, 3, 4, 5])
# Element-wise addition
print(array + 5)
# Element-wise multiplication
print(array * 2)
```
### Advanced Operations
```python
import numpy as np
array = np.array([[1, 2, 3], [4, 5, 6]])
# Transpose
print(array.T)
# Dot product
print(np.dot(array, array.T))
```
For more examples and detailed tutorials, please refer to the [official Numpy documentation](https://numpy.org/doc/stable/).
## Features
- Support for multi-dimensional arrays and matrices
- A collection of mathematical functions to operate on arrays
- Tools for integrating C/C++ and Fortran code
- Useful linear algebra, random number, and Fourier transform capabilities
## ⚖ ➤ License
This project is licensed under the MIT License. See [LICENSE](LICENSE) for details.
## ❤️ Support
If you find this repository helpful, show your support by starring it! For questions or feedback, reach out on [Twitter(`X`)](https://twitter.com/F4izy).
#### $\color{skyblue}{\textbf{Connect with me:}}$
➤ If you have questions or feedback, feel free to reach out!!!
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