MathCo Associate Data Scientist Interview Questions and Answers

Q1. What is Overfitting in decision tree
Ans. 
Overfitting in decision trees occurs when the model learns noise in the training data rather than the underlying pattern.
• Overfitting happens when the decision tree is too complex and captures noise in the training data.

• It leads to poor generalization on unseen data, as the model is too specific to the training set.

• To prevent overfitting, techniques like pruning, setting a minimum number of samples per leaf, or using en
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Q2. What is bagging
Ans. 
Bagging is a machine learning ensemble technique where multiple models are trained on different subsets of the training data and their predictions are combined.
• Bagging stands for Bootstrap Aggregating.

• It helps reduce overfitting by combining the predictions of multiple models.

• Random Forest is a popular algorithm that uses bagging by training multiple decision trees on random subsets of the data.
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Q3. What is neuron How its used in DL
Ans. 
A neuron is a basic unit of a neural network that receives input, processes it, and produces an output.
• Neurons are inspired by biological neurons in the human brain.

• They receive input signals, apply weights to them, sum them up, and pass the result through an activation function.

• Neurons are organized in layers in a neural network, with each layer performing specific tasks.

• In deep learning, multiple layers of neurons ar...read more
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Q1. System design of Netflix
Ans. 
Netflix system design involves microservices architecture, recommendation algorithms, content delivery networks, and user personalization.
• Netflix uses a microservices architecture to break down its system into smaller, independent services that can be developed and deployed separately.

• Recommendation algorithms analyze user data to suggest personalized content based on viewing history and preferences.

• Content delivery ne...read more
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Q2. Aptitude an general mathematics
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OTT platform vs Multiplex

Python coding and sql coding

Q1. List all the string which start with 'a'
Ans. 
List of strings starting with 'a'
• Use a loop to iterate through each string

• Check if each string starts with 'a'

• Add the string to the list if it starts with 'a'
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Q2. Find out max value from the given table
Ans. 
Use SQL query to find max value from a table
• Use SQL query SELECT MAX(column_name) FROM table_name;

• For example, SELECT MAX(salary) FROM employees;

• Ensure proper column name and table name are used in the query
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15 MCQ, 2 coding round

Q1. What is PCA explain eigen values
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Q2. How chatbot works really
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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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