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import numpy as np
import pandas as pd
import tensorflow as tf
import matplotlib.pyplot as plt
from sklearn.datasets import load_boston
%matplotlib


    

In [ ]:

    

def read_data(file_path,Delimiter=None):
    return np.genfromtxt(file_path,Delimiter)

def load_data():
    boston = load_boston()
    features,labels = np.array(boston.data),np.array(boston.target)
    return features,labels
    
def normalize(dataset):
    mu = np.mean(dataset,axis=0)
    sigma = np.std(dataset,axis=)
    return (dataset-mu)/sigma
def append_bias_reshape(features,labels):