OneDirect (India) Interview Questions and Answers

Q1. Give a brief about yourself.
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Q2. Salary Expectation and earliest joining date
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Q1. Brief about a project worked in the company.
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Q2. What is Data Leakage?
Ans. 
Data leakage occurs when information from outside the training dataset is used to create a model, leading to unrealistic performance.
• Occurs when information that would not be available in a real-world scenario is used in the model training process

• Can result in overly optimistic performance metrics for the model

• Examples include using future data, target leakage, and data preprocessing errors
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Q3. What is Encoder Decoder? What is a Transformer model and explain its architecture?
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Encoder Decoder is a neural network architecture used for sequence-to-sequence tasks. Transformer model is a type of neural network architecture that relies entirely on self-attention mechanisms.
• Encoder Decoder is commonly used in machine translation tasks where the input sequence is encoded into a fixed-length vector representation by the encoder and then decoded into the target sequence by the decoder.

• Transformer mod...read more
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Q4. Name some Deep learning models?
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Deep learning models include CNN, RNN, LSTM, GAN, and Transformer.
• Convolutional Neural Networks (CNN) - used for image recognition tasks

• Recurrent Neural Networks (RNN) - used for sequential data like time series

• Long Short-Term Memory (LSTM) - a type of RNN with memory cells

• Generative Adversarial Networks (GAN) - used for generating new data samples

• Transformer - used for natural language processing tasks
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Q5. What is Regularization in machine learning?
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Regularization is a technique used in machine learning to prevent overfitting by adding a penalty term to the model's loss function.
• Regularization helps to reduce the complexity of the model by penalizing large coefficients.

• It adds a penalty term to the loss function, which discourages the model from fitting the training data too closely.

• Common types of regularization include L1 (Lasso) and L2 (Ridge) regularization.

• Re...read more
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Q6. What is Model Quantization?
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Model quantization is the process of reducing the precision of the weights and activations of a neural network model to improve efficiency.
• Reduces memory usage and speeds up inference by using fewer bits to represent numbers

• Can be applied to both weights and activations in a neural network model

• Examples include converting 32-bit floating point numbers to 8-bit integers
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Basic aptitude questions were asked of easy level.

Q1. Dbms , oops , C++ , sql , aws , powerpoint
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Q1. Tell me about the job role you currently have
Ans. 
I am currently working as a React Js Frontend Developer at a tech company.
• Developing user-friendly web applications using React Js

• Collaborating with backend developers to integrate frontend with backend services

• Implementing responsive design and ensuring cross-browser compatibility

• Optimizing web applications for maximum speed and scalability
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Q2. Basics of JavaScript and reactJS
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Q1. Self introduction
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Q2. Techincal sql and unix
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Q1. Explain about indexs
Ans. 
Indexes are data structures used to improve the speed of data retrieval operations in databases.
• Indexes are created on columns in a database table to speed up the retrieval of rows matching a certain condition.

• They work by creating a separate data structure that allows the database to quickly locate rows that match the indexed column values.

• Examples of indexes include primary keys, unique keys, and non-unique indexes o...read more
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Q2. Explain about joins
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Joins are used in databases to combine rows from two or more tables based on a related column between them.
• Joins are used to retrieve data from multiple tables based on a related column between them

• Common types of joins include INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN

• 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 th...read more
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Q1. Oops concept, comparator vs comparable , design principles. TDD , Circuit breaker design , integration testing , diff between hibernate and jpa , springboot annotations , restApi basics .
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Q1. Basic hr questions
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Q1. Tell me about your previous experience?
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Q2. Why do you want to leave your past company?
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Q1. Questions relating to Finance process, Payroll, etc.
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Q1. About my previous experiences
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Q1. About roles and responsibilities
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