Q2) MinMaxScalar and StandardScalar 

Q4) PCA Algorithm (sklearn library function PCA)

Q6) Simple Linear Regression algorithm using the Gradient Descent Algorithm

Q8) Calculate the Gini Index attribute selection measure used in the construction of a decision tree. 

Q10) Using the sklearn library build a classifier using the k-Nearest Neighbor algorithm to classify the iris data set. Print both correct and wrong predictions. Use the Python ML library classes can be used for this problem.. 

Q12) Using the sklearn library build a logistic regression classifier for the Iris data set stored as a .CSV file. Display the performance of the model in terms of accuracy, precision, recall, F1 Score, AUC and also display the confusion matrix.

Q14) Agglomerative clustering, compute the ward linkage using Euclidean distance, and visualize it using a dendrogram