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        "author": "Preston Parry",
        "author_email": "ClimbsBytes@gmail.com",
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        "classifiers": [
            "Development Status :: 3 - Alpha",
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            "License :: OSI Approved :: MIT License",
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        "description": "# empathyMachines\n> A standalone NLP sentiment classifier you can import as a module\n\n## Purposes\n\n1. Offer a batteries-included NLP classifier you can use either on it's own, or to make sentiment predictions as part of a broder NLP project (for example, when classifying customer messages, whether the customer is angry or not might help you determine if this is a compensation request, or a request to adjust their address.)\n1. Have the entire sentiment prediction process scaffolded so you can feed in your own training corpus, and easily train an NLP sentiment classifier.\n\n## How to use\n\n1. Download the repo from GitHub (pip install coming later)\n1. `cd` into repo, and `pip install -r requirements.txt`\n1. In your Python code, `from EmpathyMachines import EmpathyMachines`\n1. `nlp_classifier = EmpathyMachines()`\n1. `nlp_classifier.train(corpus='Twitter')`\n1. `nlp_classifier.predict(text_string)`\n\n\n### Corpora included\n\n\n### Include your own corpus (UNDER CONSTRUCTION)\n\nFeel free to train a classifier on your own corpus!\n\nTwo ways to do this:\n1. Read in a .csv file with header row containing \"sentiment\", \"text\", and optionally, \"confidence\"\n1. Pass in an array of Python dictionaries, with attributes for \"sentiment\", \"text\", and optionally, \"confidence\"\n\n\n1. Create a .csv file with the following fields\n1. `nlp_classifier.train(corpus='custom', corpus_path='path/to/custom/corpus.csv', analytics_output=False)`",
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        "home_page": "https://github.com/ClimbsRocks/EmpathyMachines",
        "keywords": "machine learning,data science,NLP,natural language processing,sentiment,sentiment analysis,sentiment prediction,twitter corpus,twitter,tweets corpus,movie reviews corpus,NLTK,automated machine learning",
        "license": "MIT",
        "maintainer": null,
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        "name": "empathy-machines",
        "package_url": "https://pypi.org/project/empathy-machines/",
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        "summary": "An off-the-rack NLP sentiment classifier- upload your own corpus or use the pre-installed ones",
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