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I use tools like Python, SQL, Tableau for data analysis and visualization.
Python for data cleaning and analysis
SQL for querying databases
Tableau for creating interactive visualizations
A numeric value can be treated as a text value in Microsoft Excel if it precedes with an apostrophe.
Precede the numeric value with an apostrophe (') to treat it as text.
For example, entering '123 in a cell will display as text '123 instead of the numeric value 123.
This is useful when you want to display leading zeros in a number without Excel automatically removing them.
I am proficient in Python, SQL, and R for data analysis.
Proficient in Python for data cleaning and analysis
Strong in SQL for querying databases
Experienced in R for statistical analysis and visualization
Central Limit Theorem states that the sampling distribution of the sample mean approaches a normal distribution as the sample size increases.
The theorem states that regardless of the shape of the population distribution, the sampling distribution of the sample mean will be approximately normally distributed.
It is a fundamental concept in statistics and is used in hypothesis testing and confidence intervals.
For exa...
To find the last 3 records, sort the data in descending order and select the first 3 records.
Sort the data in descending order based on the relevant field
Select the first 3 records from the sorted data
Finding the longest common subsequence in a string is a standard dynamic programming problem.
Use dynamic programming to build a 2D array to store the length of the longest common subsequence at each pair of indices.
Traverse the array to reconstruct the longest common subsequence.
Example: For strings 'ABCD' and 'ACD', the longest common subsequence is 'ACD'.
I applied via Recruitment Consulltant and was interviewed in Nov 2024. There were 2 interview rounds.
Write a program to print 1 to 100 prime numbers
I appeared for an interview in Mar 2025, where I was asked the following questions.
Deep learning excels in handling complex data patterns, automating feature extraction, and improving accuracy over traditional methods.
Deep learning can automatically extract features from raw data, reducing the need for manual feature engineering. For example, in image recognition, convolutional neural networks (CNNs) can identify edges, shapes, and objects without explicit programming.
It is particularly effective for...
Random Forest is a versatile and powerful ensemble learning method for classification and regression tasks.
Handles large datasets with higher dimensionality effectively.
Reduces overfitting by averaging multiple decision trees, improving model generalization.
Provides feature importance scores, helping in feature selection and understanding model behavior.
Robust to noise and outliers, making it suitable for real-world da...
I appeared for an interview in Mar 2025, where I was asked the following questions.
There are 30 questions
There are 2 coding questions
Basic Python n data analysis tools
Data analysis for basic concepts
I applied via Campus Placement
Verbal ability,Logical reasoning
Topic:Women Empowerment
I applied via Naukri.com and was interviewed in Mar 2024. There was 1 interview round.
Central Limit Theorem states that the sampling distribution of the sample mean approaches a normal distribution as the sample size increases.
The theorem states that regardless of the shape of the population distribution, the sampling distribution of the sample mean will be approximately normally distributed.
It is a fundamental concept in statistics and is used in hypothesis testing and confidence intervals.
For example,...
I appeared for an interview in Oct 2024, where I was asked the following questions.
Outliers in box plots are identified as points beyond 1.5 times the interquartile range from the quartiles.
The whiskers of a box plot typically extend to 1.5 times the interquartile range (IQR) from the first and third quartiles.
Any data point beyond this range is considered an outlier.
For example, if Q1 is 10 and Q3 is 20, the IQR is 10. The whiskers extend to 10 - (1.5 * 10) = -5 and 20 + (1.5 * 10) = 25.
Thus, any po...
Encoding categorical variables transforms non-numeric data into a numeric format for machine learning algorithms.
Machine learning algorithms require numerical input; encoding converts categories to numbers.
Common methods include One-Hot Encoding (e.g., 'Color' with values 'Red', 'Blue' becomes binary columns).
Label Encoding assigns a unique integer to each category (e.g., 'Low' = 0, 'Medium' = 1, 'High' = 2).
Prevents m...
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