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This one trains the DNN on iris and also create confusion matrix. Comments will help you know what is happening. === #imports from __future__ import absolute_import from __future__ import division from __future__ import print_function import tensorflow as tf import numpy as np import pandas as pd from sklearn.model_selection import train_test_split # Load data # Download it from here : https://archive.ics.uci.edu/ml/datasets/iris. Ensure that the categories are #labeled as Iris-setosa, Iris-virginica, Iris-versicolor and their column name as Species. iris = pd.read_csv("irisdata.csv") # explore what is loaded #print(iris.shape) #print(iris.head) # Convert the data type of columns to float32 type #print(iris.dtypes) #print(iris.iloc[:,0:4]) iris.iloc[:,0:4] = iris.iloc[:,0:4].astype(np.float32) #print(iris.dtypes) # encode the classes to numeric values iris["Species"] = iris["Species"].map({"Iris-setosa":0,"...

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