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I applied via LinkedIn and was interviewed before Jul 2023. There were 2 interview rounds.
SQL, Python Coding program
Case study on data science
Top trending discussions
I applied via Campus Placement and was interviewed before Jul 2023. There were 3 interview rounds.
Mostly data related question and two coding questions which we had to do in python only
Attention in data science refers to the mechanism that allows models to focus on specific parts of the input data.
Attention mechanisms help models to weigh the importance of different input features.
They are commonly used in natural language processing tasks such as machine translation and text summarization.
Attention can improve the performance of models by allowing them to selectively focus on relevant information.
Ex...
Efficiency of LLMs can be judged based on various factors such as accuracy, speed, resource consumption, and interpretability.
Evaluate accuracy by comparing LLM predictions with ground truth labels
Assess speed by measuring the time taken for LLM to process data
Analyze resource consumption in terms of memory and computational power usage
Consider interpretability by examining how easily LLM decisions can be understood
Use...
I applied via Campus Placement and was interviewed before Jul 2023. There were 2 interview rounds.
Hacker Rank Test on coding questions
Coding a training pipeline involves creating a process to train machine learning models efficiently.
Define the data preprocessing steps
Split the data into training and validation sets
Choose a machine learning algorithm to train the model
Tune hyperparameters to optimize model performance
Evaluate the model using metrics like accuracy or loss
I applied via Campus Placement and was interviewed before Oct 2022. There were 4 interview rounds.
Basic leet code questions easy to a bit of medium
Handling class imbalance involves techniques like resampling, using different algorithms, and adjusting class weights.
Use resampling techniques like oversampling the minority class or undersampling the majority class.
Try using different algorithms that are less sensitive to class imbalance, such as Random Forest or XGBoost.
Adjust class weights in the model to give more importance to the minority class.
Adam optimizer is an extension to the Gradient Descent optimizer with adaptive learning rates and momentum.
Adam optimizer combines the benefits of both AdaGrad and RMSProp optimizers.
Adam optimizer uses adaptive learning rates for each parameter.
Gradient Descent optimizer has a fixed learning rate for all parameters.
Adam optimizer includes momentum to speed up convergence.
Gradient Descent optimizer updates parameters b...
Use ReLU for hidden layers in deep neural networks, avoid for output layers.
ReLU is commonly used in hidden layers to introduce non-linearity and speed up convergence.
Avoid using ReLU in output layers for regression tasks as it can lead to vanishing gradients.
Consider using Leaky ReLU or Sigmoid for output layers depending on the task.
ReLU is computationally efficient and helps in preventing the vanishing gradient prob...
I applied via Company Website and was interviewed in Dec 2023. There were 3 interview rounds.
Standard question from sql and python in hackerrank
Sql and python questions were there with basic logic check
3 question were asked in 90 min time
Precision is the ratio of correctly predicted positive observations to the total predicted positive observations.
Precision is calculated as TP / (TP + FP), where TP is true positives and FP is false positives.
It measures the accuracy of positive predictions made by the model.
A high precision indicates that the model is good at predicting positive cases without many false positives.
For example, in a binary classificatio...
A large language model is a type of artificial intelligence model that is capable of understanding and generating human language at a large scale.
Large language models use deep learning techniques to process and generate text.
Examples include GPT-3 (Generative Pre-trained Transformer 3) and BERT (Bidirectional Encoder Representations from Transformers).
I applied via Approached by Company and was interviewed in Nov 2024. There were 3 interview rounds.
I applied via Naukri.com and was interviewed in Jan 2024. There was 1 interview round.
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