Muraai Information Technologies Intern Interview Questions and Answers

2 coding questions were given , Running atleast one question with all test cases passing is mandatory.

Q1. Bit manipulation question(asked to write atleast pseudo code)
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Q2. Array based question(asked to write atleast pseudo code)
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Q1. Academic finance related questions
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Q2. Question on basic academic finance
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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?
Ans. 
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?
Ans. 
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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Q1. Python program questions
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Q2. OOPS based programming questions
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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. C and Cpp all concepts
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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.
Answered by AI
Add your answer
Q2. How do we train neural networks?
Ans. 
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
Answered by AI
Add your answer
Q3. What is overfitting?
Ans. 
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
Answered by AI
Add your answer

Q1. Python program questions
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Q2. OOPS based programming questions
Add your answer