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      • One of this language’s advantages is the large number of open-source libraries available. A Python library is a group of related code modules. You can use these modules in your own programs to make coding simpler and faster – e.g. instead of writing your own function to open an Excel file, you can use one from the pandas library.
      learnpython.com/blog/python-libraries-for-beginners/
  1. Jul 6, 2023 · In this blog post, we explored seven beginner-friendly Python libraries that cover a wide range of applications, from numerical computing and data analysis to web communication, data visualization, and game development.

    • Pillow. Pillow, actually a fork of the PIL - Python Image Library. At first Pillow was based primarily on the PIL code structure. Later, however, it turned into something friendlier and better.
    • Matplotlib. Matplotlib is a Python library that uses Python Script to write graphs and two-dimensional plots. Often mathematical or scientific applications require more than single axes in a representation.
    • Numpy. Numpy is a popular Python array processing package. It provides good support for different multidimensional array objects. Numpy is not only limited to providing arrays, but also provides a variety of tools for managing these arrays.
    • OpenCV Python. OpenCV, also known as ** Open Source Computer Vision **, is a package for image processing. It monitors general functions focused on the instant view of the computer.
    • Keras. Keras is one of the most essential Python libraries there is. It’s considered a deep learning API that was specifically designed for human use rather than machine use.
    • PyTorch. This essential library is an open-source ML framework capable of speeding up research prototyping, allowing companies to enter the production deployment phase.
    • NumPy. NumPy — short for Numerical Python — is fundamental for numerical computation in Python and contains a powerful N-dimensional array object. It’s a general-purpose array-processing package that provides multidimensional objects.
    • Pandas. Anyone interested in data science knows that learning Pandas is a must. It’s the most popular and widely used library in Python, often for data cleaning and analysis.
    • Why Learn Python?
    • Benefits of Learning Python as A New Developer
    • Tips For Learning Python
    • Conclusion

    Whether you are beginner or a person who has learned a couple of programming languages, you will likely agree that learning a new programming language can be challenging. Even more so when you don't have the right resources and guidance. But with the right help, you can make it an enjoyable experience. Python was created on December 3, 1989 by Guid...

    As a beginner getting into tech, learning Python will have lots of benefits. In addition to what we just discussed, here are some more:

    While Python is a great first language to learn, that doesn't make it a walk in the park. You'll want to take the necessary steps and find the right tools to help you along your learning path. First of all, having the right resources is a good start, and a roadmap can be very helpful. For this you won't have to struggle much: roadmap.shis an open-s...

    In this guide, I've highlighted some main reasons why you should consider Python as you first language. You have also seen Python's different applications and what you can do with it. To help you get started, I would highly encourage you to take advantages of all resources available – both those listed here and others available online (including bo...

  2. Mar 24, 2024 · Here’s why libraries are essential: Save Time and Effort: Leverage pre-written, well-tested code instead of reinventing the wheel. Extend Python’s Capabilities: Libraries provide...

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  4. Oct 23, 2024 · Extensive Libraries: Python has a vast ecosystem of libraries and frameworks for various purposes, allowing developers to leverage existing tools for their projects. Versatility: Python can be used for a wide range of applications, from web development to scientific computing and machine learning.

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