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I am a recent graduate with a degree in Business Administration and a passion for marketing and project management.
Graduated with a Bachelor's degree in Business Administration
Passionate about marketing and project management
Completed internships at marketing agencies
Strong communication and organizational skills
My goal is to gain valuable experience and knowledge in the field, develop my skills, and eventually advance in my career.
Gain valuable experience and knowledge in the field
Develop my skills through training and hands-on experience
Advance in my career by taking on more responsibilities and leadership roles
My family background is diverse and multicultural, with members from various professions and backgrounds.
My parents are both doctors, specializing in different fields.
I have a sibling who is a teacher and another who is an engineer.
We have relatives living in different countries, adding to the cultural diversity of our family.
Your company is a leading software development firm specializing in creating innovative solutions for businesses.
Specializes in software development
Known for creating innovative solutions
Serves businesses across various industries
Developed a mobile app for tracking daily water intake and setting hydration goals.
Designed user-friendly interface for easy input of water consumption
Implemented reminder notifications to encourage regular hydration
Included visual graphs to track daily, weekly, and monthly water intake
Integrated with wearable devices to sync water intake data
I applied via Referral and was interviewed in Jul 2023. There was 1 interview round.
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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.
posted on 20 Apr 2024
I applied via LinkedIn
No, a business analyst does not act like a postman.
A business analyst analyzes business processes, identifies areas for improvement, and recommends solutions.
A postman delivers mail and packages to recipients.
While both roles involve communication, a business analyst focuses on improving business operations while a postman focuses on delivering mail.
Different estimation techniques include bottom-up, top-down, analogous, parametric, and expert judgment.
Bottom-up estimation involves breaking down the project into smaller tasks and estimating each individually.
Top-down estimation uses historical data or high-level information to estimate the project as a whole.
Analogous estimation relies on past similar projects to estimate the current project.
Parametric estimation u...
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
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.
posted on 3 Jul 2024
I applied via Approached by Company and was interviewed in Jun 2024. There was 1 interview round.
Modify the trigger in the software system.
Identify the current trigger functionality and the desired modification.
Update the trigger logic or conditions as needed.
Test the modified trigger to ensure it functions correctly.
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