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Tensors and Dynamic neural networks in Python with strong GPU acceleration
Visualizer for neural network, deep learning and machine learning models
The fundamental package for scientific computing with Python.
🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
Parallel computing with task scheduling
NumPy & SciPy for GPU
NumPy aware dynamic Python compiler using LLVM
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy
tensorboard for pytorch (and chainer, mxnet, numpy, ...)
Efficiently computes derivatives of NumPy code.
🍊 :bar_chart: :bulb: Orange: Interactive data analysis
Technical Analysis Library using Pandas and Numpy
Fast data visualization and GUI tools for scientific / engineering applications
Performance analysis of predictive (alpha) stock factors
N-D labeled arrays and datasets in Python
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
napari: a fast, interactive, multi-dimensional image viewer for python
🎚️ Open Source Audio Matching and Mastering
Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
ML algorithms implemented and derived from first-principles in Jupyter Notebooks and NumPy
Python audio and music signal processing library
Fast NumPy array functions written in C
Computer Vision in Python
Add built-in support for quaternions to numpy
Pandas, Polars, Spark, and Snowpark DataFrame comparison for humans and more!
Automated Testing for Set-Top Boxes and Smart TVs
Syntax highlighting for Python Docstring in VSCode.
🚀 Fermat MCP: The Ultimate Math Engine - Unifying SymPy, NumPy & Matplotlib in one powerful server! Perfect for devs & researchers.