Metadata-Version: 2.1
Name: tensorflow-kernels
Version: 0.1
Summary: A package with Tensorflow (both CPU and GPU) implementation of most popular Kernels for kernels methods (SVM, MKL...).
Home-page: https://github.com/sirCamp/tensorflow-kernels
Author: Campese Stefano
Author-email: stefano.campese.90@gmail.com
License: MIT
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Requires-Dist: tensorflow
Requires-Dist: numpy

# Tensorflow-kernels
A package with Tensorflow (both CPU and GPU) implementation of most popular Kernels for kernels methods (SVM, MKL...).

Those kernels works with tensor as inputs. Shortly I will develop a small utils in order to convert np arrays to tensors and viceversa the kernel methods output to an np.array.

The main idea of this project is to exploit the powerfull of GPUs and modern CPUs on matrix and kernels elaborations.
Actually the implemented kernels are:


+ Linear
+ RBF
+ Polynomial
+ CosineSimilarity
+ Fourier
+ Spline

# Example: 
I will add a simple example


# Credits:
The idea was born by using methods available here: [https://github.com/gmum/pykernels](https://github.com/gmum/pykernels)


