{
    "info": {
        "author": "Pranjal-Vijay",
        "author_email": "pranjalvijaykota@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3.6"
        ],
        "description": "FastSent is Sentiment Classification python library. It uses Sequential model for Sentiment classfication. FastSent is developed using GRU(Gated Recurrent Unit) model.\n\nRequirement\n------------\n\nFastSent support Python 3.6 or newer.\n\nInstallation\n------------\n\n    pip install FastSent\n\nExample\n-------------\n\nThis package is being developed for sentiment classfication using Sequential model GRU(Gated Recurrent Unit).\n\n\tdata = 'Sample.csv'\n\tlabels = 'sentiment'\n\ttext = 'content'\n\n\tf = FastSent()\n\tX_train, X_test, y_train, y_test = f.train_test_split(data, labels, text)\n\ttrained_model = f.fit_train(X_train, y_train, 500, 50, 7789, 5, 4)\n\tprediction = f.predict(trained_model, X_test, y_train, 4)\n\n\n\n\nwhere ``sample`` is a training file containing labels and text.\n\nReferences\n----------\n\nDataSet Information\n~~~~~~~~~~~~~~~~~~~\n\n[1] Sample DataSet is being used for research purpose from  `*data.world* <https://data.world/crowdflower/sentiment-analysis-in-text>`.",
        "description_content_type": "text/markdown",
        "docs_url": null,
        "download_url": "",
        "downloads": {
            "last_day": -1,
            "last_month": -1,
            "last_week": -1
        },
        "home_page": "",
        "keywords": "",
        "license": "",
        "maintainer": "",
        "maintainer_email": "",
        "name": "FastSent",
        "package_url": "https://pypi.org/project/FastSent/",
        "platform": "",
        "project_url": "https://pypi.org/project/FastSent/",
        "project_urls": null,
        "release_url": "https://pypi.org/project/FastSent/0.2.0/",
        "requires_dist": null,
        "requires_python": "",
        "summary": "FastSent is one of the solution for Sentiment classification using Recurrent Neural Networks(GRU)",
        "version": "0.2.0"
    },
    "last_serial": 4891576,
    "releases": {
        "0.1.0": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "2721f028bb8106634c13a7ee24e2e3f1",
                    "sha256": "9d8dcef5efe7cff65835f09a8a2680d13b3cfbbcdcb48c638a50200675d48e64"
                },
                "downloads": -1,
                "filename": "FastSent-0.1.0-py3-none-any.whl",
                "has_sig": false,
                "md5_digest": "2721f028bb8106634c13a7ee24e2e3f1",
                "packagetype": "bdist_wheel",
                "python_version": "py3",
                "requires_python": null,
                "size": 2160,
                "upload_time": "2019-03-02T18:18:57",
                "url": "https://files.pythonhosted.org/packages/9f/e9/a51674302c012fcf06945bed12b8949404ceb292ac25ab93e11353a8581f/FastSent-0.1.0-py3-none-any.whl"
            },
            {
                "comment_text": "",
                "digests": {
                    "md5": "7871f153a5f91a36c50bddd69ec550b8",
                    "sha256": "712897c29e63b1cfa58a1342a08f63bc20295958b0a7b75ca08e077a4c6181b5"
                },
                "downloads": -1,
                "filename": "FastSent-0.1.0.tar.gz",
                "has_sig": false,
                "md5_digest": "7871f153a5f91a36c50bddd69ec550b8",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 1408,
                "upload_time": "2019-03-02T18:18:59",
                "url": "https://files.pythonhosted.org/packages/d3/b2/50a1b179ed609b0bc02c9fda48a22233ae731ec312156b29ea81ef60e3f5/FastSent-0.1.0.tar.gz"
            }
        ],
        "0.2.0": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "cfda90e995587cd46b3459209bc59391",
                    "sha256": "3922fbaad46b2dade991b37d710ac92dd4d5ede1bbedb8ad55e12a68aa531647"
                },
                "downloads": -1,
                "filename": "FastSent-0.2.0.tar.gz",
                "has_sig": false,
                "md5_digest": "cfda90e995587cd46b3459209bc59391",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 1717,
                "upload_time": "2019-03-03T19:06:58",
                "url": "https://files.pythonhosted.org/packages/f6/c0/059235dbde1b290f910df5ccc4652f9a6a04dc3de82204de853a72598c8c/FastSent-0.2.0.tar.gz"
            }
        ]
    },
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "md5": "cfda90e995587cd46b3459209bc59391",
                "sha256": "3922fbaad46b2dade991b37d710ac92dd4d5ede1bbedb8ad55e12a68aa531647"
            },
            "downloads": -1,
            "filename": "FastSent-0.2.0.tar.gz",
            "has_sig": false,
            "md5_digest": "cfda90e995587cd46b3459209bc59391",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 1717,
            "upload_time": "2019-03-03T19:06:58",
            "url": "https://files.pythonhosted.org/packages/f6/c0/059235dbde1b290f910df5ccc4652f9a6a04dc3de82204de853a72598c8c/FastSent-0.2.0.tar.gz"
        }
    ]
}