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It is good nice and not so tough
I am a data-driven individual with a strong analytical mindset and a passion for problem-solving.
Graduate student majoring in Data Science at XYZ University
Proficient in programming languages such as Python, R, and SQL
Experience with data visualization tools like Tableau and Power BI
Completed projects involving data cleaning, analysis, and interpretation
Strong communication skills and ability to work in a team environm
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Duation 1 hr and test difficulty medium
I applied via Internshala and was interviewed before Oct 2022. There were 2 interview rounds.
Convert Json Data to Pandas Dataframe
Use the pandas library to import the json data
Use the pandas.DataFrame() function to convert the json data into a dataframe
Specify the required columns in the dataframe
I applied via Internshala and was interviewed before Feb 2022. There was 1 interview round.
I applied via Indeed and was interviewed in Jun 2023. There were 4 interview rounds.
In aptitude test the test is process to appear in interview process
In the coding test there is complex code to slove that and correct the errors
I applied via Indeed and was interviewed in Jun 2024. There were 2 interview rounds.
Python,Sql ,multiple choice
The p value is a measure used in hypothesis testing to determine the significance of the results.
The p value is the probability of obtaining results as extreme as the observed results, assuming the null hypothesis is true.
A p value of less than 0.05 is typically considered statistically significant.
A p value greater than 0.05 suggests that the results are not statistically significant.
Researchers use p values to determ...
Calculate probability of unfair coin tossed n times and do hypothesis testing
Calculate the theoretical probability of getting heads or tails for the unfair coin
Perform the actual coin toss n times and record the outcomes
Use hypothesis testing to determine if the coin is unfair based on the observed outcomes
Bagging and boosting are ensemble learning techniques used to improve the performance of machine learning models by combining multiple weak learners.
Bagging (Bootstrap Aggregating) involves training multiple models independently on different subsets of the training data and then combining their predictions through averaging or voting.
Boosting involves training multiple models sequentially, where each subsequent model c...
I applied via Indeed and was interviewed in Jul 2024. There was 1 interview round.
I applied via Company Website and was interviewed before Apr 2023. There was 1 interview round.
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