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        "author": "UlionTse",
        "author_email": "shinalone@outlook.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Environment :: Web Environment",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6"
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        "description": "**news_api**\n==================\n\n*Usage:*\n--------\n\n\n>>> from gradient_api import gradient\n\n>>> r1 = gradient.generate(expr_or_poly1d='x**2+1')\n>>> r2 = gradient.generate(expr_or_poly1d=[1,0,1])\n\n>>> print(r1 == r2)\nTrue\n\n>>> print(r1)\n{'X': -0.00011417981541647683, 'Y': 1.0000000130370303, 'Gradient': -0.00022835963083295366, 'Numloop': 51}\n\n\n\n>>> trainData = pandas.DataFrame(numpy.array([[1,3,5,7],[2,4,6,8]]))\n>>> r3 = gradient.generate_2d(trainData)\n>>> print(r3)\n{'Gradient': array([-1020.54, -1589.21, -3630.29, -5671.37]),\n 'Linear_Coef': array([-16.94, -38.6 , -60.26]),\n 'Linear_Intercept': -10.83,\n 'Numloop': 2,\n 'Y': 263786.0329,\n 'theta': array([-10.83, -16.94, -38.6 , -60.26])}\n\n\n*Tips:*\n-------\n\n>>> generate_1d(expr_or_poly1d,init_x=-0.5,step=0.01,num_iters=1e4,showPlot=False,xlimArr=None,ylimArr=None)\n\n>>> generate_2d(dataFrame,step=0.1,num_iters=1e4)",
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