bizAmica Software Data Scientist Interview Questions and Answers

Coding and AI related Questions

Q1. Detail technical questions on projects
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Q1. Questions around resume
Ans. Explained word done by me and my responsibilities
Answered by Nikhil Pawar
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Q1. Questions around python programming and my experience in data science
Ans. Explained end to end implementation of some of the projects I worked on
Answered by Nikhil Pawar
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SQL, select statment and DDL commands

Q1. Python lists and conditional statements and loos
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Q1. Explain the importance of Model Evaluation in the process of ML pipeline
Ans. 
Model evaluation is crucial in ML pipeline to assess the performance and generalization of the model.
• Helps in selecting the best model for the given problem by comparing different models based on metrics like accuracy, precision, recall, etc.

• Prevents overfitting by checking if the model is performing well on unseen data.

• Guides in fine-tuning hyperparameters to improve model performance.

• Enables understanding of model li...read more
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Expect technical questions as well as moderate level coding questions

Q1. Data science and MLOps concepts
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Q1. Behavioral and managerial rounds
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Q1. Difference between .py and .pyc
Ans. 
The .py files contain Python code, while the .pyc files are compiled bytecode files generated by Python when a .py file is imported.
• The .py files are human-readable text files containing Python code.

• The .pyc files are compiled bytecode files created by Python to improve execution speed.

• The .pyc files are automatically generated by Python when a .py file is imported.

• The .pyc files are platform-independent and can be dis
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Q2. Why we use bias in neural networks? Why do we scale our data in neural networks?
Ans. 
Bias in neural networks helps in capturing the underlying patterns in data. Scaling data helps in improving convergence and performance.
• Bias in neural networks helps in shifting the activation function to better fit the data.

• It allows the model to capture the underlying patterns in the data by providing flexibility in the decision boundary.

• Scaling data helps in improving convergence by ensuring that the gradients are o...read more
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Q3. Explain RNN and LSTM
Ans. 
RNN is a type of neural network that processes sequential data. LSTM is a type of RNN that can learn long-term dependencies.
• RNN stands for Recurrent Neural Network and is designed to handle sequential data by maintaining a hidden state that captures information about previous inputs.

• LSTM stands for Long Short-Term Memory and is a type of RNN that addresses the vanishing gradient problem by introducing a memory cell, in...read more
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Q1. Python coding questions followed by machine learning , deep learning algorithms
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