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NumPy vs Jovian: What are the differences?

What is NumPy? Fundamental package for scientific computing with Python. Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.

What is Jovian? Tooling and workflows built specifically for data science. It is a better place for your data science projects, Jupyter notebooks, machine learning models, experiment logs, results, and more.

NumPy and Jovian can be primarily classified as "Data Science" tools.

Some of the features offered by NumPy are:

  • a powerful N-dimensional array object
  • sophisticated (broadcasting) functions
  • tools for integrating C/C++ and Fortran code

On the other hand, Jovian provides the following key features:

  • Collaboration platform built for data science
  • Simple Jupyter notebook versioning
  • Compare and analyze experiments

NumPy is an open source tool with 14.1K GitHub stars and 4.65K GitHub forks. Here's a link to NumPy's open source repository on GitHub.

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Pros of Jovian
Pros of NumPy
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    • 10
      Great for data analysis
    • 4
      Faster than list

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    - No public GitHub repository available -

    What is Jovian?

    It is a better place for your data science projects, Jupyter notebooks, machine learning models, experiment logs, results, and more.

    What is NumPy?

    Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.

    Need advice about which tool to choose?Ask the StackShare community!

    What companies use Jovian?
    What companies use NumPy?
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      What tools integrate with Jovian?
      What tools integrate with NumPy?

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