QuestionAnswered step-by-stepD O, N O T TkeDeep Learning by proximity of networking and advanced…D O, N O T TkeDeep Learning by proximity of networking and advanced programming WORK ON ALLALL QUESTIONS , tHEN DKINDLY DO NO T DO IF YOU DO N OT KNOW WHAT YOU ARE DOING OR I WILL REPORT Criteria Points AVOIPart 1 – Question 1Normalize the train and test data2Part 1 – Question 2Build and train a ANN model as per the above mentioned architecture10Part 1 – Question 3 observations on the below plot2Part 1 – Question 4Build and train the new ANN model as per the above mentioned architecture10Part 1 – Question 5 observations on the below plot2Part 1 – Question 6Print the classification report and the confusion matrix for the test predictions. observations on the final results# Import libraries for data manipulation import pandas as pd import numpy as np # Import libraries for data visualization import matplotlib.pyplot as plt import seaborn as sns from statsmodels.graphics.gofplots import ProbPlot # Import libraries for building linear regression model from statsmodels.formula.api import ols import statsmodels.api as sm from sklearn.linear_model import LinearRegression # Import library for preparing data from sklearn.model_selection import train_test_split # Import library for data preprocessing from sklearn.preprocessing import MinMaxScaler import warnings warnings.filterwarnings(“ignore”) Loading the dataIn :df = pd.read_csv(“Boston.csv”) df.head() Out: CRIM ZN INDUS CHAS NOX RM AGE DIS RAD TAX PTRATIO LSTAT MEDV0 0.00632 18.0 2.31 0 0.538 6.575 65.2 4.0900 1 296 15.3 4.98 24.01 0.02731 0.0 7.07 0 0.469 6.421 78.9 4.9671 2 242 17.8 9.14 21.62 0.02729 0.0 7.07 0 0.469 7.185 61.1 4.9671 2 242 17.8 4.03 34.73 0.03237 0.0 2.18 0 0.458 6.998 45.8 6.0622 3 222 18.7 2.94 33.44 0.06905 0.0 2.18 0 0.458 7.147 54.2 6.0622 3 222 18.7 5.33 36.2 Observation:The price of the house indicated by the variable MEDV is the target variable and the rest of the variables are independent variables based on which we will predict the house price (MEDV).Checking the info of the dataIn :df.info()
Delivering a high-quality product at a reasonable price is not enough anymore.
That’s why we have developed 5 beneficial guarantees that will make your experience with our service enjoyable, easy, and safe.
You have to be 100% sure of the quality of your product to give a money-back guarantee. This describes us perfectly. Make sure that this guarantee is totally transparent.Read more
Each paper is composed from scratch, according to your instructions. It is then checked by our plagiarism-detection software. There is no gap where plagiarism could squeeze in.Read more
Thanks to our free revisions, there is no way for you to be unsatisfied. We will work on your paper until you are completely happy with the result.Read more
Your email is safe, as we store it according to international data protection rules. Your bank details are secure, as we use only reliable payment systems.Read more
By sending us your money, you buy the service we provide. Check out our terms and conditions if you prefer business talks to be laid out in official language.Read more