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25 | 25 | - [Imbalanced Datasets](#imbalanced-datasets) |
26 | 26 | - [Random Forests](#random-forests) |
27 | 27 | - [Kernel Methods](#kernel-methods) |
28 | | - - [Extreme Learning Machine](#extreme-learning-machine) |
29 | 28 | - [Deep Learning](#deep-learning) |
30 | 29 | - [PyTorch](#pytorch) |
31 | 30 | - [TensorFlow](#tensorflow) |
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128 | 127 | * [scikit-rvm](https://github.com/JamesRitchie/scikit-rvm) - Relevance Vector Machine implementation using the scikit-learn API. <img height="20" src="img/sklearn_big.png" alt="sklearn"> |
129 | 128 | * [ThunderSVM](https://github.com/Xtra-Computing/thundersvm) - A fast SVM Library on GPUs and CPUs. <img height="20" src="img/sklearn_big.png" alt="sklearn"> <img height="20" src="img/gpu_big.png" alt="GPU accelerated"> |
130 | 129 |
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131 | | -### Extreme Learning Machine |
132 | | -* [Python Extreme Learning Machine (ELM)](https://github.com/acba/elm) - A machine learning technique used for classification/regression tasks. |
133 | | -* [hpelm](https://github.com/akusok/hpelm) - High-performance implementation of Extreme Learning Machines (fast randomized neural networks). <img height="20" src="img/gpu_big.png" alt="GPU accelerated"> |
134 | | - |
135 | 130 | ## Deep Learning |
136 | 131 |
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137 | 132 | ### PyTorch |
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