Aganitha Cognitive Solutions Interview Questions, Process, and Tips

Objective test on DS/NLP/AI

Q1. Describe your project?
Ans. 
Developed a machine learning model to predict customer churn for a telecom company.
• Used Python and scikit-learn for data preprocessing and model building

• Performed feature engineering to create new variables for better prediction

• Evaluated model performance using metrics like accuracy, precision, and recall
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Q2. More questions on the specific project
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Asked to fill out the form consists of general data sciences, python questions

Q1. Discussion about the resume.
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It didnt require time limit to complete.

Q1. What is the difference between iLoc and Loc in pandas.
Ans. 
iLoc is used for integer-location based indexing while Loc is used for label-based indexing in pandas.
• iLoc is used for selecting data based on integer index positions.

• Loc is used for selecting data based on labels.

• iLoc uses integer index positions starting from 0.

• Loc uses labels from the index or column names.

• Example: df.iloc[0] selects the first row based on integer index position.

• Example: df.loc['row_label'] selects
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Q2. What is principal component analysis.
Ans. 
Principal component analysis is a technique used to reduce the dimensionality of data while preserving its variance.
• PCA is a dimensionality reduction technique that identifies the directions (principal components) along which the data varies the most.

• It projects the data onto these principal components to reduce the dimensionality of the data.

• PCA is commonly used in machine learning for feature extraction and data visu...read more
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Q3. Why is Variance important in principal component analysis?
Ans. 
Variance in principal component analysis helps to identify the most important features in the data.
• Variance measures the spread of data points around the mean, indicating the importance of each feature in capturing the overall variability.

• Higher variance implies more information is retained by the principal components, making them more significant in representing the data.

• By selecting components with high variance, we ...read more
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Q4. What have you been doing for the last six months?
Ans. 
I have been working on developing a machine learning model for predicting customer churn in a telecom company.
• Developed machine learning algorithms using Python and TensorFlow

• Cleaned and preprocessed large datasets to train the model

• Performed feature engineering to improve model performance

• Conducted A/B testing to evaluate model effectiveness
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Q5. What is the syntax to read a CSV file from python?
Ans. 
Use the pandas library to read a CSV file in Python.
• Import the pandas library: import pandas as pd

• Use the read_csv() function to read the CSV file: df = pd.read_csv('file.csv')

• Specify additional parameters like delimiter, header, etc. if needed
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Have to fill a quiz interviewers send

Q1. Strengths and weaknesses
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Q2. Salary expectations
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Q3. Location preference
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Q1. Discuss previous work experience
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Q2. Questions related to previous work experience
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Q1. Discuss the research article the interviewers share
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Q2. Share opinions about the work reported in that article, and suggest possible improvements
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Q1. Salary negotiations
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