Neterson Technologies Interview Questions and Answers

Q1. Python program questions
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Q2. OOPS based programming questions
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Q1. What is polymorphism
Ans. 
Polymorphism is the ability of a function or method to behave differently based on the object it is acting upon.
• Polymorphism allows objects of different classes to be treated as objects of a common superclass.

• It enables a single interface to be used for different data types or classes.

• Examples include method overloading and method overriding in object-oriented programming.
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Q2. Find missing number from nth number array.
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Find missing number from nth number array.
• Iterate through the array and calculate the sum of all numbers

• Calculate the sum of numbers from 1 to n using the formula n*(n+1)/2

• Subtract the sum of array from the sum of numbers from 1 to n to find the missing number
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Q3. Explain inheritance and it types
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Inheritance is a concept in object-oriented programming where a class inherits properties and behaviors from another class.
• Inheritance allows a class to reuse code from another class.

• Types of inheritance include single inheritance, where a class inherits from only one parent class, and multiple inheritance, where a class inherits from multiple parent classes.

• Example: Class B inherits from Class A, so Class B can access
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Q4. Find 2nd max elements from aaray
Ans. 
Find 2nd max element from array of strings
• Sort the array in descending order

• Skip the first element (max element)

• Return the second element
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Q1. C and Cpp all concepts
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Q1. DSA - Linked List, Array and Strings
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Q1. Why should we hire you
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Q1. What is hyperparameter tuning?
Ans. 
Hyperparameter tuning is the process of selecting the best set of hyperparameters for a machine learning model.
• Hyperparameters are parameters that are set before the learning process begins.

• Hyperparameter tuning involves adjusting hyperparameters to optimize the model's performance.

• Common techniques for hyperparameter tuning include grid search, random search, and Bayesian optimization.
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Q2. How do we train neural networks?
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Neural networks are trained using algorithms that adjust the weights and biases of the network based on the input data and desired output.
• Neural networks are trained using a process called backpropagation, where the error between the predicted output and the actual output is used to adjust the weights and biases of the network.

• Training data is fed into the neural network, and the network's output is compared to the des...read more
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Q3. What is overfitting?
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Overfitting occurs when a machine learning model learns the training data too well, including noise and outliers, leading to poor generalization on new data.
• Overfitting happens when a model is too complex and captures noise in the training data.

• It can be identified when a model performs well on training data but poorly on unseen data.

• Techniques to prevent overfitting include cross-validation, regularization, and early ...read more
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Aptitude was quite easy with simple python questions

Asked basic questions on numpy and pandas