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README.md

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 # gaussian_kde_gpu
-GPU Gaussian kernel density estimation
+
+## GPU Gaussian kernel density estimation
+
+The provided function `gaussian_kde_gpu()` is a simplified version of Scipy's `gaussian_kde`. It does not support weights and only uses the default Scott's Rule for bandwidth estimation. However, it leverages the computative power of a CUDA supported GPU via Numba. Given the random variable `p` it will estimate the probability density function (PDF) at query point `q` in the following way:
+
+``` {.python .numberLines}
+from gaussian_kde_gpu import gaussian_kde_gpu
+
+density = = gaussian_kde_gpu(p, q)
+```
+
+For more details see [tutorial](GPU_Gaussian_kernel_density_estimation.ipynb).
+
+### Requirements
+
+- Numpy
+- Numba