nestedcvtraining
NumPy
nestedcvtraining | NumPy | |
---|---|---|
6 | 272 | |
27 | 26,360 | |
- | 0.9% | |
0.0 | 10.0 | |
over 1 year ago | 7 days ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
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nestedcvtraining
- [P] Nested Cross Validation Library
- Project: Nested Cross Validation Library
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[D] Andrew Ng's data-centric vs model-centric Machine Learning
Once you have your pipeline, model included, with all the transformers defined and parametrized, you could use an optimizing approach like the one in the examples of this library: https://github.com/JaimeArboleda/nestedcvtraining Do you think it will be a good idea? Or am I oversimplifying?
- [D] What’s the simplest, most lightweight but complete and 100% open source MLOps toolkit?
- [P] New library for performing nested cross validation, optimizing, calibrating and reporting quality of binary classification models
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?
Python Packages Project Generator - 🚀 Your next Python package needs a bleeding-edge project structure.
SymPy - A computer algebra system written in pure Python
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
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
projects - Sample projects using Ploomber.
blaze - NumPy and Pandas interface to Big Data
summer - A compartmental disease modelling framework (Python)
SciPy - SciPy library main repository
clearml - ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
Numba - NumPy aware dynamic Python compiler using LLVM
speech-enhancement - Experiments with speech enhancement
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).