NumPy
Engineering Software · Texas, United States · 1-10 Employees
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Overview
Headquarters
Austin, Texas, United StatesWebsite
www.numpy.orgRevenue
<$5 MillionIndustry
ZI Rank: 1
Signal Type
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ZI Rank
1
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About NumPy
NumPy is a fundamental package for scientific computing with Python, offering powerful N-dimensional arrays and a wide range of mathematical functions. It is designed for a diverse community of scientists and programmers, providing tools for numerical computing, data science, and machine learning. As an open-source library, NumPy is optimized for performance and interoperability with various hardware and computing platforms. Its high-level syntax makes it accessible to users of all experience levels, facilitating the development of advanced analytics and visualization applications.Explore more
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Revenue
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Founded In
NumPy
<$5M
1-10
Private
-
2005
N/A
Products Owned by NumPy
NumPy
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NumPy Tech Stack
A closer look at the technologies used by NumPy
NumPy News & Media
NumPy: 10 Most Common Usage Patterns 🐍 - Kasper Junge - Medium
NumPy arrays are at the core of this library, enabling efficient storage and manipulation of data. You can create arrays using various techniques, such as from existing lists or with built-in… - medium.comUse Cython to accelerate array iteration in NumPy
NumPy is known for being fast, but could it go even faster? Here's how to use Cython to accelerate array iterations in NumPy. NumPy gives Python users a wickedly fast library for working with data in matrixes. If you want, for instance, to generate a matrix populated with random numbers, you can do that in a fraction of the time it would take in conventional Python. Still, there are times when even NumPy by itselfUse Cython to accelerate array iteration in NumPy
NumPy is known for being fast, but could it go even faster? Here's how to use Cython to accelerate array iterations in NumPy. NumPy gives Python users a wickedly fast library for working with data in matrixes. If you want, for instance, to generate a matrix populated with random numbers, you can do that in a fraction of the time it would take in conventional Python. Still, there are times when even NumPy by itselfWhat is Google JAX? NumPy on accelerators
Among the innovations that power the popular open source TensorFlow machine learning platform are automatic differentiation (Autograd) and the XLA (Accelerated Linear Algebra) optimizing compiler for deep learning. To read this article in full, please click here
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NumPy is a fundamental package for scientific computing with Python, offering powerful N-dimensional arrays and a wide range of mathematical functions. It is designed for a diverse community of scientists and programmers, providing tools for numerical computing, data science, and machine learning. As an open-source library, NumPy is optimized for p... Read More
