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This repo is dedicated to providing helpful resources, tutorials, and examples for using the Numpy library in Python.\n\n## Table of Contents\n\n- [Numpy](#numpy)\n  - [Table of Contents](#table-of-contents)\n  - [Roadmap](#roadmap)\n  - [Introduction](#introduction)\n  - [Installation](#installation)\n  - [Usage](#usage)\n    - [Creating an Array](#creating-an-array)\n    - [Basic Operations](#basic-operations)\n    - [Advanced Operations](#advanced-operations)\n  - [Features](#features)\n\n\n## Roadmap\n\n![Numpy-roadmap](https://github.com/mohd-faizy/Learn_Numpy/blob/main/_img/Numpy-Roadmap.png)\n\n## Introduction\n\nNumpy 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.\n\nThis 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.\n\n## Installation\n\nTo install Numpy, you can use pip, the Python package installer. Ensure you have Python installed, then run:\n\n```bash\npip install numpy\n```\n\nFor more detailed installation instructions, please refer to the [official Numpy installation guide](https://numpy.org/install/).\n\n## Usage\n\nHere are some basic examples to get you started with Numpy:\n\n### Creating an Array\n\n```python\nimport numpy as np\n\narray = np.array([1, 2, 3, 4, 5])\nprint(array)\n```\n\n### Basic Operations\n\n```python\nimport numpy as np\n\narray = np.array([1, 2, 3, 4, 5])\n\n# Element-wise addition\nprint(array + 5)\n\n# Element-wise multiplication\nprint(array * 2)\n```\n\n### Advanced Operations\n\n```python\nimport numpy as np\n\narray = np.array([[1, 2, 3], [4, 5, 6]])\n\n# Transpose\nprint(array.T)\n\n# Dot product\nprint(np.dot(array, array.T))\n```\n\nFor more examples and detailed tutorials, please refer to the [official Numpy documentation](https://numpy.org/doc/stable/).\n\n## Features\n\n- Support for multi-dimensional arrays and matrices\n- A collection of mathematical functions to operate on arrays\n- Tools for integrating C/C++ and Fortran code\n- Useful linear algebra, random number, and Fourier transform capabilities\n\n## ⚖ ➤ License\n\nThis project is licensed under the MIT License. See [LICENSE](LICENSE) for details.\n\n## ❤️ Support\n\nIf you find this repository helpful, show your support by starring it! For questions or feedback, reach out on [Twitter(`X`)](https://twitter.com/F4izy).\n\n#### $\\color{skyblue}{\\textbf{Connect with me:}}$\n\n➤ If you have questions or feedback, feel free to reach out!!!\n\n[\u003cimg align=\"left\" src=\"https://cdn4.iconfinder.com/data/icons/social-media-icons-the-circle-set/48/twitter_circle-512.png\" width=\"32px\"/\u003e][twitter]\n[\u003cimg align=\"left\" src=\"https://cdn-icons-png.flaticon.com/512/145/145807.png\" width=\"32px\"/\u003e][linkedin]\n[\u003cimg align=\"left\" src=\"https://cdn-icons-png.flaticon.com/512/2626/2626299.png\" width=\"32px\"/\u003e][Portfolio]\n\n[twitter]: https://twitter.com/F4izy\n[linkedin]: https://www.linkedin.com/in/mohd-faizy/\n[Portfolio]: https://ai.stackexchange.com/users/36737/faizy?tab=profile\n\n---\n\n\u003cimg src=\"https://github-readme-stats.vercel.app/api?username=mohd-faizy\u0026show_icons=true\" width=380px height=200px /\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmohd-faizy%2Flearn_numpy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmohd-faizy%2Flearn_numpy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmohd-faizy%2Flearn_numpy/lists"}