Anko Lead Data Scientist Interview Questions and Answers

Q1. How to reduce model inference latency
Ans. 
To reduce model inference latency, optimize model architecture, use efficient algorithms, batch processing, and deploy on high-performance hardware.
• Optimize model architecture by reducing complexity and removing unnecessary layers

• Use efficient algorithms like XGBoost or LightGBM for faster predictions

• Implement batch processing to make predictions in bulk rather than one at a time

• Deploy the model on high-performance har
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Q2. Different sql joins and their difference
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SQL joins are used to combine rows from two or more tables based on a related column between them.
• INNER JOIN: Returns rows when there is at least one match in both tables.

• LEFT JOIN: Returns all rows from the left table and the matched rows from the right table.

• RIGHT JOIN: Returns all rows from the right table and the matched rows from the left table.

• FULL JOIN: Returns rows when there is a match in one of the tables.

• SEL
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Q1. Intermediate level SQL questions using joins and case when
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Q2. String manipulation advanced level question in python
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A/B Testing, data structures

Q1. What is bias and variance how regularization helps in reducing overfitting
Ans. 
Bias is error due to overly simplistic assumptions, variance is error due to sensitivity to fluctuations. Regularization helps by penalizing complex models.
• Bias is error from erroneous assumptions in the learning algorithm. Variance is error from sensitivity to fluctuations in the training set.

• High bias can cause underfitting, where the model is too simple to capture the underlying structure. High variance can cause ov...read more
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Q2. Random Forest XGBoost pros and cons, hyperparameters. Data imputation methods
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Q3. Difference between RNN and LSTM, advantage and limitations.
Ans. 
RNN is a type of neural network that processes sequential data, while LSTM is a type of RNN that addresses vanishing gradient problem.
• RNN is a type of neural network that can process sequential data by maintaining a hidden state.

• LSTM (Long Short-Term Memory) is a type of RNN that addresses the vanishing gradient problem by introducing memory cells and gates.

• LSTM is capable of learning long-term dependencies in data, ma...read more
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3 Leet code mediums in 30 mins.

Q1. 5 ML questions in 10 mins
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Q2. 5 Stats question in 10 mins
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Q3. 3 LC mediums in 30 minutes
Ans. 
LC mediums refer to LeetCode mediums, which are medium difficulty coding problems on the LeetCode platform.
• LC mediums are coding problems with medium difficulty level on LeetCode platform.

• Solving 3 LC mediums in 30 minutes requires good problem-solving skills and efficient coding techniques.

• Examples of LC mediums include 'Longest Substring Without Repeating Characters' and 'Container With Most Water'.
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Q1. Why do you want to leave your current job?
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SQL coding question. Medium level

Explain my project and then case study regarding launching new apps

Q1. Linear regression
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Q2. Probability related questions
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Q3. Sampling and AB testing
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Q1. Backpropagation in neural network
Ans. 
Backpropagation is a method used to train neural networks by adjusting the weights based on the error in the output.
• Backpropagation involves calculating the gradient of the loss function with respect to the weights of the network.

• The gradient is then used to update the weights in the opposite direction to minimize the error.

• This process is repeated iteratively until the network converges to a solution.

• Backpropagation i...read more
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Q2. Clustering (k-means, DB scan)
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1 question on array (sorting related), 1 question on string (hard problem)

Q1. Behavioral questions
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Q1. Resume related questions with the hiring manager
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Python for Data Science basics

Optimization case study