HyperVerge Data Scientist Interview Questions and Answers

General aptitude basics

Mcq and basic ml model building

Q1. Explain Transformers how different from previous RNN, LSTM etc.
Ans. 
Transformers are a type of neural network architecture that utilizes self-attention mechanisms to process sequential data.
• Transformers use self-attention mechanisms to weigh the importance of different input elements, allowing for parallel processing of sequences.

• Unlike RNNs and LSTMs, Transformers do not rely on sequential processing, making them more efficient for long-range dependencies.

• Transformers have been shown ...read more
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Q2. What are different types of Attention?
Ans. 
Different types of Attention include self-attention, global attention, and local attention.
• Self-attention focuses on relationships within the input sequence itself.

• Global attention considers the entire input sequence when making predictions.

• Local attention only attends to a subset of the input sequence at a time.

• Examples include Transformer's self-attention mechanism, Bahdanau attention, and Luong attention.
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Q3. Difference between GPT and BERT model
Ans. 
GPT is a generative model while BERT is a transformer model for natural language processing.
• GPT is a generative model that predicts the next word in a sentence based on previous words.

• BERT is a transformer model that considers the context of a word by looking at the entire sentence.

• GPT is unidirectional, while BERT is bidirectional.

• GPT is better for text generation tasks, while BERT is better for understanding the cont
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Q1. Difference between Data scientist, ML and AI
Ans. 
Data scientists analyze data to gain insights, machine learning (ML) involves algorithms that improve automatically through experience, and artificial intelligence (AI) refers to machines mimicking human cognitive functions.
• Data scientists analyze large amounts of data to uncover patterns and insights.

• Machine learning involves developing algorithms that improve automatically through experience.

• Artificial intelligence r...read more
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Easy to solve if you have basic mathematics understanding.

They will test your presence of mind and thinking.

Aptitude test consists of 40 questions.

Q1. Introduce yourself with ur projects
Ans. 
I am a data scientist with experience in developing predictive models and analyzing large datasets.
• Developed a predictive model for customer churn prediction using machine learning algorithms

• Analyzed sales data to identify key trends and patterns for business optimization

• Implemented natural language processing techniques for sentiment analysis of customer reviews
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Q2. Problem statement of a case that needs solutions.
Ans. 
Develop a predictive model to identify potential customers for a new product launch.
• Define the target variable and features to be used in the model

• Collect and preprocess relevant data for training the model

• Select an appropriate machine learning algorithm and train the model

• Evaluate the model's performance using metrics like accuracy, precision, and recall

• Use the model to predict potential customers for the new product
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