Reserve Bank Information Technology Data Scientist Interview Questions and Answers

Test time 35 min, based on Python SQL Stats

Q1. Explain ML algorithms
Ans. 
ML algorithms are mathematical models used to identify patterns and make predictions from data.
• ML algorithms can be supervised, unsupervised, or semi-supervised

• Supervised algorithms include linear regression, decision trees, and neural networks

• Unsupervised algorithms include k-means clustering and principal component analysis

• Semi-supervised algorithms combine elements of both supervised and unsupervised learning

• ML algo...read more
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Q2. Explain SQL joins, explain join in a given situation
Ans. 
SQL joins are used to combine data from two or more tables based on a related column.
• Joins are used to retrieve data from multiple tables in a single query.

• Common types of joins are inner join, left join, right join, and full outer join.

• Joining tables can be done using the JOIN keyword and specifying the columns to join on.

• Example: SELECT * FROM table1 JOIN table2 ON table1.column = table2.column;

• Joins can be used to c...read more
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Q1. Explain projects you have worked
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Q2. The algorithm used in the project (in my case LSTM)
Ans. 
The algorithm used in the project is LSTM.
• LSTM stands for Long Short-Term Memory and is a type of recurrent neural network.

• It is commonly used for sequential data analysis such as time series forecasting, speech recognition, and natural language processing.

• LSTM networks have the ability to remember long-term dependencies and avoid the vanishing gradient problem.

• They consist of memory cells, input gates, output gates, a...read more
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Q3. Why LSTM? how does it work?
Ans. 
LSTM is a type of recurrent neural network that can handle long-term dependencies.
• LSTM stands for Long Short-Term Memory.

• It uses gates to control the flow of information.

• It can remember information for a longer period of time compared to traditional RNNs.

• It is commonly used in natural language processing and speech recognition tasks.

• LSTM has been shown to be effective in predicting stock prices and weather patterns.
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