arXiv Open Access 2018

Pymc-learn: Practical Probabilistic Machine Learning in Python

Daniel Emaasit
Lihat Sumber

Abstrak

$\textit{Pymc-learn}$ is a Python package providing a variety of state-of-the-art probabilistic models for supervised and unsupervised machine learning. It is inspired by $\textit{scikit-learn}$ and focuses on bringing probabilistic machine learning to non-specialists. It uses a general-purpose high-level language that mimics $\textit{scikit-learn}$. Emphasis is put on ease of use, productivity, flexibility, performance, documentation, and an API consistent with $\textit{scikit-learn}$. It depends on $\textit{scikit-learn}$ and $\textit{pymc3}$ and is distributed under the new BSD-3 license, encouraging its use in both academia and industry. Source code, binaries, and documentation are available on http://github.com/pymc-learn/pymc-learn.

Topik & Kata Kunci

Penulis (1)

D

Daniel Emaasit

Format Sitasi

Emaasit, D. (2018). Pymc-learn: Practical Probabilistic Machine Learning in Python. https://arxiv.org/abs/1811.00542

Akses Cepat

Lihat di Sumber
Informasi Jurnal
Tahun Terbit
2018
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓