pytorch/pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
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Tensors and Dynamic neural networks in Python with strong GPU acceleration
The fundamental package for scientific computing with Python.
Visualizer for neural network, deep learning and machine learning models
🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
Home Assistant integration for smart-plug appliance monitoring: detects cycles, matches programs, estimates time remaining. Supports washing machines, dryers, dishwashers and more.
Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy
NumPy aware dynamic Python compiler using LLVM
🎚️ Open Source Audio Matching and Mastering
Main repository for Mantid code
napari: a fast, interactive, multi-dimensional image viewer for python
TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...
Efficiently computes derivatives of NumPy code.
N-D labeled arrays and datasets in Python
JAX in JavaScript – ML library for the web, running on WebGPU & Wasm
🍊 :bar_chart: :bulb: Orange: Interactive data analysis
Fast data visualization and GUI tools for scientific / engineering applications
Pandas, Polars, Spark, and Snowpark DataFrame comparison for humans and more!
MessagePack serialization library for Python derived from orjson, written in Rust using PyO3
Python/C++ library for distribution power system analysis
A high-performance, zero-overhead, extensible Python compiler with built-in NumPy support
Open Data Cube analyses continental scale Earth Observation data through time
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
Manipulate JSON-like data with NumPy-like idioms.
Convert Machine Learning Code Between Frameworks
Fast NumPy array functions written in C
C++ tensors with broadcasting and lazy computing
Neural network from scratch in pure Python + NumPy that recognises handwritten digits (MNIST), with an educational GUI: watch it learn, tweak it while it trains, look inside every layer.
WebGL 3D plotting for Jupyter: meshes, isosurfaces, volumes, voxels and point clouds from NumPy arrays, with a path-traced cinematic renderer.
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