variables-with-units-language-p
NumPy
| variables-with-units-language-p | NumPy | |
|---|---|---|
| 1 | 272 | |
| - | 26,510 | |
| - | 1.4% | |
| - | 10.0 | |
| - | 6 days ago | |
| Python | ||
| - | GNU General Public License v3.0 or later |
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variables-with-units-language-p
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Microfeatures I'd like to see in more languages
Declaration of units for primitive numeric variables.
https://github.com/mchrisman/variables-with-units-language-p...
NumPy
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In NumPy with @, dot() or matmul():
- NumPy 2.0.0 Beta1
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Element-wise vs Matrix vs Dot multiplication
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication.
- JSON dans les projets data science : Trucs & Astuces
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JSON in data science projects: tips & tricks
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:
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Introducing Flama for Robust Machine Learning APIs
numpy: A library for scientific computing in Python
- help with installing numpy, please
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A Comprehensive Guide to NumPy Arrays
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy.
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Why do all the popular projects use relative imports in __init__ files if PEP 8 recommends absolute?
I was looking at all the big projects like numpy, pytorch, flask, etc.
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NumPy 2.0 development status & announcements: major C-API and Python API cleanup
I wish the NumPy devs would more thoroughly consider adding full fluent API support, e.g. x.sqrt().ceil(). [Issue #24081]
What are some alternatives?
coherence - Oracle Coherence Community Edition
SymPy - A computer algebra system written in pure Python
manifold - Manifold is a Java compiler plugin, its features include Metaprogramming, Properties, Extension Methods, Operator Overloading, Templates, a Preprocessor, and more.
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
S-Lang - The S-Lang programming library is a software library for Unix, Windows, VMS, OS/2, and Mac OS X. It provides routines for embedding an interpreter for the S-Lang scripting language, and components to facilitate the creation of text-based applications.[3] The latter class of functions include routines for constructing and manipulating keymaps, an interactive line-editing facility, and both low- and high-level screen/terminal management functions. It is distributed under the terms of the GNU General Public License.
blaze - NumPy and Pandas interface to Big Data
variables-with-units-language-proposal - A proposed langage feature for variables with units
SciPy - SciPy library main repository
physical
Numba - NumPy aware dynamic Python compiler using LLVM
scalars - Physical Scalars and Plotting Tools in Scala
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).