梯度下降Python代码合计

梯度下降的Python代码合计包括了以下几个部分的代码实现：

1. 批量梯度下降实现代码：根据引用中的示例数据data.csv，可以使用numpy库来实现梯度下降算法。代码如下：

import numpy as np

def gradient_descent(X, y, alpha, iterations):
    m = len(y)
    theta = np.zeros((X.shape * 100

if __name__ == "__main__":
    data = pd.read_csv("..\\dataset\\raw\\train.csv", index_col='id')
    null_info = collect_na_value(data)
    plt.figure()
    plt.plot(null_info)
    plt.show()

3. 特征编码代码：根据引用中的示例代码，可以使用pandas和numpy库来对特征数据进行编码转换。代码如下：

import pandas as pd
import numpy as np

a2z = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
a2z_code = np.arange(1, 27)
a2z_mapping = dict(zip(a2z, a2z_code))

data.loc[:, ['grade', 'subGrade']] = data.loc[:, ['grade', 'subGrade']].applymap(lambda g: g.replace(g<span class="em">1</span><span class="em">2</span><span class="em">3</span>
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