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OneDirect (India)
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I applied via Company Website and was interviewed before Mar 2023. There were 3 interview rounds.
DS & algorithm questions
Scaling the API involves optimizing performance, increasing capacity, and ensuring reliability.
Implementing caching mechanisms to reduce server load and improve response times
Using load balancers to distribute incoming traffic evenly across multiple servers
Optimizing database queries and indexes to handle increased data volume
Implementing horizontal scaling by adding more servers to handle increased traffic
Monitoring p...
I am interested in this position because it aligns with my skills and passion for [specific field/industry].
I have a strong background in [relevant skills/industry experience].
I am passionate about [specific field/industry] and want to contribute to its growth.
This position offers opportunities for professional development and growth.
I am excited about the company's mission and values.
I believe my skills and experience
Top trending discussions
posted on 14 Jan 2025
I applied via Campus Placement and was interviewed in Dec 2024. There were 4 interview rounds.
It includes multiple-choice questions for the field you are applying to.
Some basic data structure and algorithm questions; you can choose your preferred language to code.
I applied via LinkedIn and was interviewed in Dec 2024. There were 2 interview rounds.
Based on my CV, they assigned me a task related to data migration.
I applied via Company Website and was interviewed in May 2024. There were 2 interview rounds.
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
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...
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
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...
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
Basic aptitude questions were asked of easy level.
I applied via Recruitment Consulltant and was interviewed in Apr 2024. There were 2 interview rounds.
posted on 14 Feb 2024
I applied via Naukri.com and was interviewed in Jan 2024. There were 3 interview rounds.
I applied via Campus Placement and was interviewed in Dec 2023. There were 4 interview rounds.
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