Hyperthink Systems Data Scientist Interview Questions and Answers

Q1. What is overfitting in machine learning?
Ans. 
Overfitting occurs when a machine learning model learns the training data too well, including noise and outliers, leading to poor generalization on new data.
• Overfitting happens when a model is too complex and captures noise in the training data.

• It leads to poor performance on unseen data as the model fails to generalize well.

• Techniques to prevent overfitting include cross-validation, regularization, and early stopping.

• ...read more
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Q2. Overfitting accurs when a model learns the details.......etc
Ans. 
Overfitting occurs when a model learns the details and noise in the training data to the extent that it negatively impacts the model's performance on new data.
• Overfitting happens when a model is too complex and captures noise in the training data.

• It leads to poor generalization and high accuracy on training data but low accuracy on new data.

• Techniques to prevent overfitting include cross-validation, regularization, and...read more
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Q1. How would you handle missing dataduring analysis?
Ans. 
Handling missing data involves identifying, assessing, and applying appropriate techniques to manage gaps in datasets.
• Identify missing data: Use methods like 'isnull()' in Python to find missing values.

• Assess the impact: Determine how missing data affects your analysis and results.

• Imputation: Replace missing values with mean, median, or mode. For example, use the median for skewed distributions.

• Remove missing data: If ...read more
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Q2. Explain the difference inner join and left join in SQL ? and example
Ans. 
Inner join returns matching records from both tables, while left join returns all records from the left table and matching from the right.
• Inner Join: Combines rows from two tables where there is a match in both tables.

• Left Join: Returns all rows from the left table and matched rows from the right table; unmatched rows from the right will show NULL.

• Example of Inner Join: SELECT * FROM TableA INNER JOIN TableB ON TableA....read more
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Q3. Which visualisation have tools used and how do you decide which chart to used for a given dataset?
Ans. 
Choosing the right visualization depends on data type, audience, and insights needed.
• Use bar charts for categorical comparisons (e.g., sales by region).

• Line charts are ideal for trends over time (e.g., monthly revenue).

• Pie charts can show proportions but are less effective for many categories.

• Scatter plots help identify relationships between two variables (e.g., age vs. income).

• Heatmaps visualize data density or correl...read more
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Based on my CV, they assigned me a task related to data migration.

Q1. Project reviews
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Q2. Attendance regarding
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Q1. How do you handle missing r increasing data in a dataset?
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Q2. Which tools and technique do you use for data visualization?
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Q1. What is the pivot table in Excel
Ans. 
A pivot table in Excel is a data summarization tool that allows you to reorganize and summarize selected columns and rows of data.
• Allows users to summarize and analyze large datasets

• Can easily reorganize data by dragging and dropping fields

• Provides options to calculate sums, averages, counts, etc. for data

• Helps in creating interactive reports and charts

• Useful for identifying trends and patterns in data
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Q2. A pivot table is used to summarize...........etc.
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Q1. "how do you handle missing or corrupted data in a dataset?"
Ans. 
I handle missing or corrupted data by identifying, analyzing, and applying appropriate techniques to ensure data integrity.
• Identify missing data using methods like 'isnull()' in Python's pandas library.

• Analyze the extent of missing data to determine if it's significant enough to impact results.

• Use imputation techniques, such as replacing missing values with the mean or median, to maintain dataset size.

• Consider removing...read more
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Q2. "can you explain the difference between inner join, left join, Right join, and full join in SQL?"
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Q1. "How do you handle missing or inconsistent data in a dataset?"
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Q2. "can you explain a project where your analysis directly influenced a business decision?"
Ans. 
Analyzed customer feedback data to improve product features, leading to a 20% increase in customer satisfaction and sales.
• Conducted a sentiment analysis on customer reviews to identify common pain points.

• Presented findings to the product team, highlighting the need for improved user interface.

• Collaborated with marketing to adjust messaging based on customer preferences.

• Tracked sales data post-implementation, showing a ...read more
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Q1. Machine Learning
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Q1. Machine Learning
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Approach check for multiple case studies