alphafold2
To eventually become an unofficial Pytorch implementation / replication of Alphafold2, as details of the architecture get released (by lucidrains)
NumPy
The fundamental package for scientific computing with Python. (by numpy)
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| alphafold2 | NumPy | |
|---|---|---|
| 1 | 272 | |
| 1,501 | 26,360 | |
| - | 1.9% | |
| 0.0 | 10.0 | |
| over 1 year ago | 4 days ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
alphafold2
Posts with mentions or reviews of alphafold2.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-09.
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A basic introduction to NumPy's einsum
* Example: https://github.com/lucidrains/alphafold2/blob/d59cb1ea536bc5...
NumPy
Posts with mentions or reviews of NumPy.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-03-20.
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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]