Protium Finance Data Scientist Interview Questions and Answers

Q1. Tell me about your self
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Q1. What is Bert and transformer
Ans. 
Bert and transformer are models used in natural language processing for tasks like text classification and language generation.
• Bert (Bidirectional Encoder Representations from Transformers) is a transformer-based model developed by Google for NLP tasks.

• Transformer is a deep learning model architecture that uses self-attention mechanisms to process sequential data like text.

• Both Bert and transformer have been widely use...read more
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Q2. NLP pre processing techniques
Ans. 
NLP pre processing techniques involve cleaning and preparing text data for analysis.
• Tokenization: breaking text into words or sentences

• Stopword removal: removing common words that do not add meaning

• Lemmatization: reducing words to their base form

• Normalization: converting text to lowercase

• Removing special characters and punctuation
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Q1. Basic questions
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Q2. Strength weakness
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Q1. SQL Window functions
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Q2. Excel computed fields in pivot tables
Ans. 
Excel pivot tables allow users to create computed fields using formulas.
• In Excel pivot tables, computed fields are created by adding a new field with a formula.

• Formulas can be simple arithmetic operations or more complex calculations.

• Computed fields can be used to perform calculations on existing data in the pivot table.

• Examples: calculating profit margin by dividing revenue by cost, calculating average sales per month
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Q3. Difference in precision and recall
Ans. 
Precision is the ratio of correctly predicted positive observations to the total predicted positives, while recall is the ratio of correctly predicted positive observations to the all observations in actual class.
• Precision focuses on the accuracy of positive predictions, while recall focuses on the proportion of actual positives that were correctly identified.

• Precision = TP / (TP + FP)

• Recall = TP / (TP + FN)

• Example: In...read more
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Q1. About past experience
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Q2. Past project details
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Q1. Tell me about your self
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Q1. What is Bert and transformer
Ans. 
Bert and transformer are models used in natural language processing for tasks like text classification and language generation.
• Bert (Bidirectional Encoder Representations from Transformers) is a transformer-based model developed by Google for NLP tasks.

• Transformer is a deep learning model architecture that uses self-attention mechanisms to process sequential data like text.

• Both Bert and transformer have been widely use...read more
Answered by AI
Add your answer
Q2. NLP pre processing techniques
Ans. 
NLP pre processing techniques involve cleaning and preparing text data for analysis.
• Tokenization: breaking text into words or sentences

• Stopword removal: removing common words that do not add meaning

• Lemmatization: reducing words to their base form

• Normalization: converting text to lowercase

• Removing special characters and punctuation
Answered by AI
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Q1. Basic questions
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Q2. Strength weakness
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Basic Questions on probability statistics etv.

All path summing to a value in a binaru tree