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Tech Mahindra Data Scientist Interview Questions and Answers

Updated 4 Aug 2024

Q1. What is linear regression? How to process data? Explain KLM algorithm.

Ans.

Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables.

  • Linear regression is used to predict the value of a dependent variable based on the value of one or more independent variables.

  • It assumes a linear relationship between the independent and dependent variables.

  • The goal of linear regression is to find the best-fitting line that minimizes the sum of squared differences between the observed va...read more

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Q2. What is the context window in LLMs

Ans.

Context window in LLMs refers to the number of surrounding words considered when predicting the next word in a sequence.

  • Context window helps LLMs capture dependencies between words in a sentence.

  • A larger context window allows the model to consider more context but may lead to increased computational complexity.

  • For example, in a context window of 2, the model considers 2 words before and 2 words after the target word for prediction.

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Q3. What are regex patterns in python

Ans.

Regex patterns in Python are sequences of characters that define a search pattern.

  • Regex patterns are used for pattern matching and searching in strings.

  • They are created using the 're' module in Python.

  • Examples of regex patterns include searching for email addresses, phone numbers, or specific words in a text.

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Q4. Difference between supervised and unsupervised learning

Ans.

Supervised learning uses labeled data to train a model, while unsupervised learning uses unlabeled data.

  • Supervised learning requires a target variable for training the model.

  • Examples of supervised learning include classification and regression.

  • Unsupervised learning finds patterns and relationships in data without a target variable.

  • Examples of unsupervised learning include clustering and dimensionality reduction.

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Q5. What is top_k parameter

Ans.

top_k parameter is used to specify the number of top elements to be returned in a result set.

  • top_k parameter is commonly used in machine learning algorithms to limit the number of predictions or recommendations.

  • For example, in recommendation systems, setting top_k=5 will return the top 5 recommended items for a user.

  • In natural language processing tasks, top_k can be used to limit the number of possible next words in a sequence.

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Q6. What are iterators and tuples

Ans.

Iterators are objects that allow iteration over a sequence of elements. Tuples are immutable sequences of elements.

  • Iterators are used to loop through elements in a collection, like lists or dictionaries

  • Tuples are similar to lists but are immutable, meaning their elements cannot be changed

  • Example of iterator: for item in list: print(item)

  • Example of tuple: my_tuple = (1, 2, 3)

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Q7. What is sigmoid function

Ans.

Sigmoid function is a mathematical function that maps any real value to a value between 0 and 1.

  • Used in machine learning for binary classification problems to produce probabilities

  • Commonly used in logistic regression

  • Has an S-shaped curve

  • Equation: f(x) = 1 / (1 + e^(-x))

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