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I applied via Walk-in and was interviewed in Apr 2023. There were 4 interview rounds.
Made a machine learning model
Handling imbalanced data involves resampling techniques like oversampling or undersampling. Imputation techniques include mean, median, mode, or predictive modeling.
For imbalanced data, consider using techniques like oversampling (SMOTE) or undersampling to balance the classes.
Imputation techniques include filling missing values with mean, median, mode, or using predictive modeling like KNN or Random Forest.
Evaluate th...
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Code for parsing a triangle
Use a loop to iterate through each line of the triangle
Split each line into an array of numbers
Store the parsed numbers in a 2D array or a list of lists
The ASCII value is a numerical representation of a character. It includes both capital and small alphabets.
ASCII values range from 65 to 90 for capital letters A to Z.
ASCII values range from 97 to 122 for small letters a to z.
For example, the ASCII value of 'A' is 65 and the ASCII value of 'a' is 97.
I applied via Naukri.com and was interviewed in Nov 2023. There were 2 interview rounds.
SQL, select statment and DDL commands
posted on 19 Oct 2023
I applied via Recruitment Consulltant and was interviewed before Oct 2022. There were 3 interview rounds.
I applied via Recruitment Consultant and was interviewed in Mar 2021. There was 1 interview round.
I applied via Naukri.com and was interviewed before Jul 2023. There was 1 interview round.
The .py files contain Python code, while the .pyc files are compiled bytecode files generated by Python when a .py file is imported.
The .py files are human-readable text files containing Python code.
The .pyc files are compiled bytecode files created by Python to improve execution speed.
The .pyc files are automatically generated by Python when a .py file is imported.
The .pyc files are platform-independent and can be dis
Bias in neural networks helps in capturing the underlying patterns in data. Scaling data helps in improving convergence and performance.
Bias in neural networks helps in shifting the activation function to better fit the data.
It allows the model to capture the underlying patterns in the data by providing flexibility in the decision boundary.
Scaling data helps in improving convergence by ensuring that the gradients are o...
RNN is a type of neural network that processes sequential data. LSTM is a type of RNN that can learn long-term dependencies.
RNN stands for Recurrent Neural Network and is designed to handle sequential data by maintaining a hidden state that captures information about previous inputs.
LSTM stands for Long Short-Term Memory and is a type of RNN that addresses the vanishing gradient problem by introducing a memory cell, in...
I was interviewed before Feb 2024.
Case study was given to test coding and ML skills
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