Inkle Data Science Intern Interview Questions and Answers for Freshers

Q1. ML and deep learning questions
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Q1. Projects discussion
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Q2. Chatgpt architecture
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Basic DSA questions will be asked Leetcode Easy to medium

Q1. BERT vs LSTM and their speed
Ans. 
BERT is faster than LSTM due to its transformer architecture and parallel processing capabilities.
• BERT utilizes transformer architecture which allows for parallel processing of words in a sentence, making it faster than LSTM which processes words sequentially.

• BERT has been shown to outperform LSTM in various natural language processing tasks due to its ability to capture long-range dependencies more effectively.

• For exa...read more
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Q2. What is multinomial Naive Bayes theorem
Ans. 
Multinomial Naive Bayes is a classification algorithm based on Bayes' theorem with the assumption of independence between features.
• It is commonly used in text classification tasks, such as spam detection or sentiment analysis.

• It is suitable for features that represent counts or frequencies, like word counts in text data.

• It calculates the probability of each class given the input features and selects the class with the
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Q1. What are Large Language Models?
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Large Language Models are advanced AI models that can generate human-like text based on input data.
• Large Language Models use deep learning techniques to understand and generate text.

• Examples include GPT-3 (Generative Pre-trained Transformer 3) and BERT (Bidirectional Encoder Representations from Transformers).

• They are trained on vast amounts of text data to improve their language generation capabilities.
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Q2. Do you know about RAGs?
Ans. 
RAGs stands for Red, Amber, Green. It is a project management tool used to visually indicate the status of tasks or projects.
• RAGs is commonly used in project management to quickly communicate the status of tasks or projects.

• Red typically indicates tasks or projects that are behind schedule or at risk.

• Amber signifies tasks or projects that are on track but may require attention.

• Green represents tasks or projects that ar...read more
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Q3. Which is the best clustering algorithm?
Ans. 
There is no one-size-fits-all answer as the best clustering algorithm depends on the specific dataset and goals.
• The best clustering algorithm depends on the dataset characteristics such as size, dimensionality, and noise level.

• K-means is popular for its simplicity and efficiency, but may not perform well on non-linear data.

• DBSCAN is good for clusters of varying shapes and sizes, but may struggle with high-dimensional d...read more
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Q1. Basic python and machine learning questions
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Q1. Salary expectation and working location related questions and why you want to join wipro
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The first technical round will cover how computer vision works, including the advantages and disadvantages of regression and random forest. It will also include discussions on when to use precision and recall, methods to reduce false positives, and criteria for selecting different models. Additionally, disadvantages of PCA will be addressed, along with project-related questions. The second round will focus on standard aptitude tests, while the third round will involve a casual conversation with the Executive Vice President.

Normal aptitude questions

Q1. What is L1 and L2 Regularization?
Ans. 
L1 and L2 regularization are techniques used in machine learning to prevent overfitting by adding penalty terms to the cost function.
• L1 regularization adds the absolute values of the coefficients as penalty term to the cost function.

• L2 regularization adds the squared values of the coefficients as penalty term to the cost function.

• L1 regularization can lead to sparse models by forcing some coefficients to be exactly zer...read more
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Q1. What are hyperparameters in random forest
Ans. 
Hyperparameters in random forest are parameters that are set before the learning process begins.
• Hyperparameters control the behavior of the random forest algorithm.

• They are set by the data scientist and are not learned from the data.

• Examples of hyperparameters in random forest include the number of trees, the maximum depth of trees, and the number of features considered at each split.
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Q2. How to do QnA system with LLM
Ans. 
A QnA system with LLM is a system that uses the Language Model for Information Retrieval and Question Answering.
• Preprocess the input question and convert it into a format suitable for the LLM model.

• Fine-tune the LLM model on a dataset of question-answer pairs.

• Use the fine-tuned model to generate answers for new questions.

• Evaluate the performance of the QnA system using metrics like precision, recall, and F1 score.

• Itera...read more
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Q3. How to do unit testing
Ans. 
Unit testing is a process of testing individual units of code to ensure they function correctly.
• Write test cases for each unit of code

• Test inputs, outputs, and edge cases

• Use testing frameworks like JUnit or pytest

• Automate tests to run regularly

• Ensure tests are independent, isolated, and repeatable
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