Le is Machine Learning Framework designed so that programs using it will be easy to read. Library is written in pure C but in object-oriented way. Bindings to other languages are provided so Le can be used by C++, Rust and Python programs.
Le is now under heavy development. Please come back soon.
At this moment following ML models are implemented:
- Polynomial Regression.
- Support Vector Machines (SVM).
- Sequential Feed-forward Neural Network (Multiple Layer Perceptron, MLP).
- k-Nearest Neighbors Algorithm (k-NN).
Optimization algorithms supported:
- Batch Gradient Descent (BGD).
- Stochastic Gradient Descent (SGD) with momentum.
- Sequential Minimal Optimization (SMO).
Supported backends:
- NVIDIA CUDA.
- Apple Metal.
Copyright © 2017 Kyrylo Polezhaiev. All rights reserved.
Le is released under the MIT License.