prediction-btc


Nameprediction-btc JSON
Version 0.0.1 PyPI version JSON
download
home_pageNone
SummaryA small example package
upload_time2025-01-18 21:36:22
maintainerNone
docs_urlNone
authorNone
requires_python>=3.8
licenseNone
keywords prediction bitcoin ai
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            ## Prediction_BTC Package untuk menganalisis sentimen Bitcoin dari teks menggunakan preprocessing, tokenization, dan model machine learning. 

## Fitur Utama 
- Membersihkan teks dari noise seperti tanda baca dan angka. 
- Tokenisasi teks dengan padding otomatis. 
- Analisis sentimen menggunakan model machine learning terlatih. 
- Mendukung klasifikasi sentimen positif dan negatif. 

## Instalasi Gunakan pip untuk menginstal package ini: pip install prediction_btc 

## Penggunaan Berikut adalah contoh sederhana penggunaan package ini: python from prediction_btc import full_prediction 

# Teks yang ingin dianalisis text = ["Bitcoin is the future!", "The market is crashing!"] 
# Prediksi sentimen result = full_prediction(text) print(result) 

## Dependencies Package ini membutuhkan library berikut: 
- Python 3.7+ 
- TensorFlow 
- Numpy 
- Pandas 
- Scikit-learn 
- Joblib  

## Lisensi Project ini dirilis di bawah lisensi MIT. 
## Kontak Jika memiliki pertanyaan atau feedback, silakan hubungi saya: Komang Nitay Prasaddas Email: nitay06@students.amikom.ac.id

            

Raw data

            {
    "_id": null,
    "home_page": null,
    "name": "prediction-btc",
    "maintainer": null,
    "docs_url": null,
    "requires_python": ">=3.8",
    "maintainer_email": null,
    "keywords": "prediction, bitcoin, ai",
    "author": null,
    "author_email": "Komang Nitay Prasaddas <nitay06@students.amikom.ac.id>",
    "download_url": "https://files.pythonhosted.org/packages/11/79/cf2a059912ac08e2caffeb1366f77bf1780152124c5281719cf026341888/prediction_btc-0.0.1.tar.gz",
    "platform": null,
    "description": "## Prediction_BTC Package untuk menganalisis sentimen Bitcoin dari teks menggunakan preprocessing, tokenization, dan model machine learning. \r\n\r\n## Fitur Utama \r\n- Membersihkan teks dari noise seperti tanda baca dan angka. \r\n- Tokenisasi teks dengan padding otomatis. \r\n- Analisis sentimen menggunakan model machine learning terlatih. \r\n- Mendukung klasifikasi sentimen positif dan negatif. \r\n\r\n## Instalasi Gunakan pip untuk menginstal package ini: pip install prediction_btc \r\n\r\n## Penggunaan Berikut adalah contoh sederhana penggunaan package ini: python from prediction_btc import full_prediction \r\n\r\n# Teks yang ingin dianalisis text = [\"Bitcoin is the future!\", \"The market is crashing!\"] \r\n# Prediksi sentimen result = full_prediction(text) print(result) \r\n\r\n## Dependencies Package ini membutuhkan library berikut: \r\n- Python 3.7+ \r\n- TensorFlow \r\n- Numpy \r\n- Pandas \r\n- Scikit-learn \r\n- Joblib  \r\n\r\n## Lisensi Project ini dirilis di bawah lisensi MIT. \r\n## Kontak Jika memiliki pertanyaan atau feedback, silakan hubungi saya: Komang Nitay Prasaddas Email: nitay06@students.amikom.ac.id\r\n",
    "bugtrack_url": null,
    "license": null,
    "summary": "A small example package",
    "version": "0.0.1",
    "project_urls": {
        "Homepage": "https://github.com/pypa/sampleproject",
        "Issues": "https://github.com/pypa/sampleproject/issues"
    },
    "split_keywords": [
        "prediction",
        " bitcoin",
        " ai"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "26924ab2569343b9e52fb6c9dc0d4cd9e108fed16c0ba926d8eb6d2432d859a3",
                "md5": "6fc539c693998bf418b62630be83e5a7",
                "sha256": "e90dca41f6ab676f5a1037ab3eac119a975824d6f17f2243be6658adb1d4698d"
            },
            "downloads": -1,
            "filename": "prediction_btc-0.0.1-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "6fc539c693998bf418b62630be83e5a7",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": ">=3.8",
            "size": 96085762,
            "upload_time": "2025-01-18T21:35:55",
            "upload_time_iso_8601": "2025-01-18T21:35:55.245804Z",
            "url": "https://files.pythonhosted.org/packages/26/92/4ab2569343b9e52fb6c9dc0d4cd9e108fed16c0ba926d8eb6d2432d859a3/prediction_btc-0.0.1-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "1179cf2a059912ac08e2caffeb1366f77bf1780152124c5281719cf026341888",
                "md5": "332717ce43aa5376b4709ad516337061",
                "sha256": "b1b4daadb5eed8fe671faedd4fe6b56f2367ab4da7c5b305423840ef6330124c"
            },
            "downloads": -1,
            "filename": "prediction_btc-0.0.1.tar.gz",
            "has_sig": false,
            "md5_digest": "332717ce43aa5376b4709ad516337061",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": ">=3.8",
            "size": 96089730,
            "upload_time": "2025-01-18T21:36:22",
            "upload_time_iso_8601": "2025-01-18T21:36:22.038932Z",
            "url": "https://files.pythonhosted.org/packages/11/79/cf2a059912ac08e2caffeb1366f77bf1780152124c5281719cf026341888/prediction_btc-0.0.1.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2025-01-18 21:36:22",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "pypa",
    "github_project": "sampleproject",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": true,
    "lcname": "prediction-btc"
}
        
Elapsed time: 0.37376s