10 Python libraries to learn in 2023

Popular Python libraries that are widely used in a variety of applications

There are many popular Python libraries that are widely used in a variety of applications. Some of the most popular libraries include:

1. NumPy — A library for scientific computing with Python, which provides support for large, multi-dimensional arrays and matrices of numerical data, and a large collection of mathematical functions to operate on these arrays.
2. Pandas — A library for data manipulation and analysis, which provides tools for reading and writing data, data cleaning and preparation, and data analysis and visualization.
3. Matplotlib — A library for data visualization, which provides tools for creating a wide range of static, animated, and interactive visualizations in Python.
4. Scikit-learn — A library for machine learning in Python, which provides a range of tools and algorithms for supervised and unsupervised learning, as well as tools for model selection and evaluation.
5. TensorFlow — A library for machine learning and deep learning, which provides support for building and training neural networks, and tools for optimizing and deploying machine learning models.
6. PyTorch — A library for machine learning and deep learning, which provides support for building and training neural networks, and tools for optimizing and deploying machine learning models.
7. Django — A web framework for Python, which provides tools for building and deploying web applications quickly and easily.
8. Flask — A micro web framework for Python, which provides a lightweight way to build web applications and APIs.
9. Requests — A library for making HTTP requests in Python, which makes it easy to send HTTP requests and work with HTTP responses.
10. Beautiful Soup — A library for web scraping and parsing HTML and XML, which makes it easy to extract data from websites and web pages.

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