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Burn is a next generation Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.
Open deep learning compiler stack for cpu, gpu and specialized accelerators
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch:入门与实战》)
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
AI + Data, online. https://vespa.ai
LibRec: A Leading Java Library for Recommender Systems, see
C++ DataFrame for statistical, financial, and ML analysis in modern C++
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
A list of awesome compiler projects and papers for tensor computation and deep learning.
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
Inference Llama 2 in one file of pure 🔥
Deep learning in Rust, with shape checked tensors and neural networks
TensorLy: Tensor Learning in Python.
A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends
The Tensor Algebra Compiler (taco) computes sparse tensor expressions on CPUs and GPUs