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I applied via Referral and was interviewed in Aug 2023. There were 2 interview rounds.
Evaluation metrics for classification ML model
Accuracy: measures the overall correctness of the model
Precision: measures the proportion of true positive predictions among all positive predictions
Recall: measures the proportion of true positive predictions among all actual positives
F1 Score: harmonic mean of precision and recall
Confusion Matrix: provides a summary of correct and incorrect predictions
Precision and recall are used in evaluating the performance of classification models.
Precision is used when the goal is to minimize false positives.
Recall is used when the goal is to minimize false negatives.
Precision is calculated as TP / (TP + FP) where TP is true positives and FP is false positives.
Recall is calculated as TP / (TP + FN) where FN is false negatives.
In medical field, precision is important when identi...
Null values can be handled by either removing them, replacing them with a default value, or imputing them with a calculated value.
Remove null values from the dataset
Replace null values with a default value (e.g. 0 for numerical data, 'Unknown' for categorical data)
Impute null values with a calculated value (e.g. mean, median, mode)
Window functions and aggregate functions in SQL
Window functions perform calculations across a set of table rows related to the current row
Aggregate functions perform a calculation on a set of values and return a single value
Examples of window functions include ROW_NUMBER(), RANK(), and LAG()
Examples of aggregate functions include SUM(), AVG(), and COUNT()
I applied via Campus Placement and was interviewed in Dec 2022. There were 3 interview rounds.
General aptitude question and reasoning questions
I applied via LinkedIn and was interviewed before Jun 2020. There were 3 interview rounds.
Top trending discussions
I was interviewed before Sep 2016.
I was interviewed in Jul 2017.
To leverage my skills and passion for technology in a field that offers diverse opportunities for growth and innovation.
Passion for technology and its advancements
Strong analytical and problem-solving skills
Desire to work in a field that offers diverse opportunities for growth and innovation
Transferable skills from other branch that can be applied in IT
Interest in staying updated with the latest trends and developments
I was interviewed before May 2016.
I have the skills, experience, and passion to excel in this role.
I have a strong background in data analysis and have successfully completed numerous projects in the past.
I am detail-oriented and have a proven track record of delivering high-quality work under tight deadlines.
I am a team player and have excellent communication skills, which allows me to collaborate effectively with colleagues and stakeholders.
I was interviewed in Mar 2017.
I was interviewed before May 2016.
I am a dedicated and detail-oriented analyst with a strong background in data analysis and problem-solving.
I have a Bachelor's degree in Statistics and have completed multiple internships in data analysis.
I am proficient in statistical software such as R and Python.
I have experience in conducting market research and creating detailed reports for stakeholders.
I am a quick learner and enjoy tackling complex problems to f
based on 3 interviews
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