Showing 21-40 of 48 projects
This repository provides the Chinese Simplified documentation for the TVM (Tensor Virtual Machine) framework, a popular open-source deep learning compiler stack.
C++ DataFrame library for statistical, financial, and machine learning analysis.
A high-performance, auto-diff neural network library for 3D and 4D sparse tensor computations.
A unified framework for large-scale data computation that scales popular Python data tools like NumPy, Pandas, and Scikit-Learn.
A curated list of awesome compiler projects and papers for tensor computation and deep learning.
Rootless replacement for Tensor Pixel VoLTE patch using Kotlin
High-performance machine learning algorithms with 2-2000x speed and 50% less memory usage for all hardware.
A comprehensive collection of LaTeX code examples for drawing Bayesian networks, graphical models, and technical illustrations.
Deep learning library for Rust with shape-checked tensors and neural networks
A Python library for efficient manipulation of tensor networks, a powerful tool for AI and machine learning.
zetane/viewer is a Python-based 3D visualizer for ML models and internal tensors.
A Python library that provides type annotations and dynamic checking for tensors' shape, dtype, and names.
High-performance N-dimensional tensor computation library for .NET, similar to NumPy for Python.
Reference Jupyter notebooks and demo AI/ML applications for enterprise use cases
A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices.
A small, lightweight tensor library in C for developers working on AI/ML projects.
A Jupyter Notebook library focused on making tensor manipulation and visualization more accessible to developers.
Tensor Algebra Compiler (taco) is a C++ library for computing sparse tensor expressions on CPUs and GPUs.
Pretty Tensor is a fluent interface for building TensorFlow models in Python, making it easier for developers to work with AI.
Aesara is a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays.
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