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Top Python & ML Interview Questions

Interview Questions

Q1- Detect loop in the linked list (figure1)

Ans-

Sample code 

class BaseNode: 

    def __init__(self, data): 

        self.data = data 

        self.next = None

class List: 

   

    # Function to initialize head 

    def __init__(self): 

        self.head = None

    

    def push(self, new_data): 

        new_node = BaseNode(new_data) 

        new_node.next = self.head 

        self.head = new_node 

    

    def printList(self): 

        temp = self.head 

        while(temp): 

            print (temp.data, end =" ") 

            temp = temp.next

   

   

    def detect_loop(self): 

         s = set() 

         temp = self.head 

         while (temp):    

            if (temp in s): 

                return True

      

            s.add(temp) 

            temp = temp.next

         return False

list =List() 

list.push(1) 

list.push(2) 

list.push(3) 

list.push(4) 

   

# Create a loop using 

list.head.next.next.next.next = list.head; 

  

if( llist.detect_loop()): 

    print ("Loop found") 

else : 

    print ("No Loop ") 

 

 

Q2- Replace the “u” with “at” and “n” with “ur” in the following string sequences.

str1=’sunday’

Ans-

str1='sunday'

str2=str1.replace('u','at').replace('n','ur')

print(str2)

 

Q3-Describe the term Bias-Variance Tradeoff in Machine Learning
Ans –


Bias, Variance is the main factor that leads to the models are underfitting and overfitting. For the good model, it must be in Low bias and low variance.

 


Q4-What is pickling and unpickling in python
Ans –


Pickling
The string representation of any object and dumps it into a file is known as pickling.


 Sample Code:


 import pickle
 data1 = {'a': 'test',
        'b': ('test'),
        'd': None}
output = open('pickle.pkl', 'wb')
pickle.dump(data1, output)
output.close()

Unpickling
While the retrieving of the String representation of the object from file is known as unpickling.

To read from a pickled file


Sample Code:

import pickle
pk_file = open('pickle.pkl', 'rb')
data1 = pickle.load(pk_file)
pk_file.close()


Thank you for reading!

Fig.2
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