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Burn is a next generation Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.
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》)
Open deep learning compiler stack for cpu, gpu and specialized accelerators
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