November 2022
Intermediate to advanced
392 pages
10h 8m
Chinese
Content preview from Python算法交易
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通过机器学习预测市场动向
｜
175
最好通过
pip install tensorflow
和
pip install keras
安装这些库。
scikit-learn
还提供将神经网络应用于分类问题的类。
有关深度学习和
Keras
的更多背景信息，请参阅
Goodfellow
等（
2016
）和
Chollet
（
2017
）。
5.3.1
再谈简单分类问题
为了说明将神经网络应用于分类问题的基本方法，上一节介绍的简单分类问题再次
被证明是有用的：
In [134]: hours = np.array([0.5, 0.75, 1., 1.25, 1.5, 1.75, 1.75, 2.,
2.25, 2.5, 2.75, 3., 3.25, 3.5, 4., 4.25,
4.5, 4.75, 5., 5.5])
In [135]: success = np.array([0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1,
0, 1, 1, 1, 1, 1, 1])
In [136]: data = pd.DataFrame({'hours': hours, 'success': success})
In [137]: data.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 20 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.