josephmisiti/awesome-machine-learning
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Merge pull request #977 from shubham0204/master

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Added six new ML frameworks for Rust
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@ -137,6 +137,8 @@ Further resources:
- [Misc](#ruby-misc)
- [Rust](#rust)
- [General-Purpose Machine Learning](#rust-general-purpose-machine-learning)
- [Deep Learning](#rust-deep-learning)
- [Natural Language Processing](#rust-natural-language-processing)
- [R](#r)
- [General-Purpose Machine Learning](#r-general-purpose-machine-learning)
- [Data Analysis / Data Visualization](#r-data-analysis--data-visualization)
@ -1519,7 +1521,19 @@ be
* [leaf](https://github.com/autumnai/leaf) - open source framework for machine intelligence, sharing concepts from TensorFlow and Caffe. Available under the MIT license. [**[Deprecated]**](https://medium.com/@mjhirn/tensorflow-wins-89b78b29aafb#.s0a3uy4cc)
* [RustNN](https://github.com/jackm321/RustNN) - RustNN is a feedforward neural network library. **[Deprecated]**
* [RusticSOM](https://github.com/avinashshenoy97/RusticSOM) - A Rust library for Self Organising Maps (SOM).
* [candle](https://github.com/huggingface/candle) - Candle is a minimalist ML framework for Rust with a focus on performance (including GPU support) and ease of use.
* [linfa](https://github.com/rust-ml/linfa) - `linfa` aims to provide a comprehensive toolkit to build Machine Learning applications with Rust
#### Deep Learning
* [tch-rs](https://github.com/LaurentMazare/tch-rs) - Rust bindings for the C++ API of PyTorch
* [dfdx](https://github.com/coreylowman/dfdx) - Deep learning in Rust, with shape checked tensors and neural networks
* [burn](https://github.com/tracel-ai/burn) - Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals
#### Natural Language Processing
* [huggingface/tokenizers](https://github.com/huggingface/tokenizers) - Fast State-of-the-Art Tokenizers optimized for Research and Production
* [rust-bert](https://github.com/guillaume-be/rust-bert) - Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)
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## R