{
    "info": {
        "author": "Roland Memisevic",
        "author_email": "roland@cs.toronto.edu",
        "bugtrack_url": null,
        "classifiers": [
            "Topic :: Scientific/Engineering :: Artificial Intelligence",
            "Topic :: Scientific/Engineering :: Information Analysis",
            "Topic :: Scientific/Engineering :: Visualization"
        ],
        "description": "Monte (python) is a framework for rapidly building learning machines, such as\r\nneural networks, conditional random fields, logistic regression, and others.\r\nMonte consists of almost 100% pure Python code (with a little bit of optional\r\ninline-C for efficiency) and is therefore extremely easy to use and to extend.",
        "description_content_type": null,
        "docs_url": null,
        "download_url": "http://sourceforge.net/projects/montepython/",
        "downloads": {
            "last_day": -1,
            "last_month": -1,
            "last_week": -1
        },
        "home_page": "http://montepython.sourceforge.net",
        "keywords": "machine learning, neural networks, conditional random fields",
        "license": "Python software foundation license.",
        "maintainer": "Roland Memisevic",
        "maintainer_email": "roland@cs.toronto.edu",
        "name": "Monte",
        "package_url": "https://pypi.org/project/Monte/",
        "platform": "",
        "project_url": "https://pypi.org/project/Monte/",
        "project_urls": {
            "Download": "http://sourceforge.net/projects/montepython/",
            "Homepage": "http://montepython.sourceforge.net"
        },
        "release_url": "https://pypi.org/project/Monte/0.0.11/",
        "requires_dist": null,
        "requires_python": null,
        "summary": "Monte - machine learning in pure Python.",
        "version": "0.0.11"
    },
    "last_serial": 27179,
    "releases": {
        "0.0.11": [],
        "0.0.3": [],
        "0.0.5": [],
        "0.0.8": []
    },
    "urls": []
}