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Yubi Data Scientist Interview Questions and Answers
Yubi Data Scientist Interview Experiences
3 interviews found
Anonymous
Selected
I applied via Referral and was interviewed in Jul 2024. There were 2 interview rounds.
(1 Question)
- Q1. Question regarding my resume .It is technical interview
Case study-this is about loan default prediction assignment
Sql and pandas problems along mcqs on ML
(2 Questions)
- Q1. Linear Regression
- Q2. Basic Neural Network Implementation
(2 Questions)
- Q1. Question about working of BERT
- Q2. Word2vec explanation
- Ans.
Word2vec is a technique used to create word embeddings by training a neural network on a large corpus of text.
Word2vec is a shallow neural network model that learns to represent words as vectors in a continuous vector space.
It captures semantic relationships between words by placing similar words close together in the vector space.
There are two main architectures for Word2vec: Continuous Bag of Words (CBOW) and Skip-gr...
Skills evaluated in this interview
Selected
I applied via Referral and was interviewed before Feb 2023. There was 1 interview round.
(2 Questions)
- Q1. What is clustering
- Ans.
Clustering is a technique used in data analysis to group similar data points together based on their characteristics.
Clustering is an unsupervised learning method.
It helps in identifying patterns and relationships in data.
Common clustering algorithms include K-means, hierarchical clustering, and DBSCAN.
Example: Grouping customers based on their purchasing behavior.
Example: Identifying different species of flowers based
- Q2. How to avoid overfitting
- Ans.
To avoid overfitting, use techniques like cross-validation, regularization, and increasing training data.
Use cross-validation to evaluate model performance on unseen data
Apply regularization techniques like L1 or L2 regularization to penalize complex models
Increase the size of the training dataset to provide more diverse examples
Use feature selection or dimensionality reduction methods to reduce the complexity of the m...
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Skills evaluated in this interview
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Interview questions from similar companies
I applied via Referral and was interviewed in Nov 2024. There was 1 interview round.
Cancellation in the number of bookings in an app has increased exponentially in the past few weeks, How would you conduct an RCA on the same.
(2 Questions)
- Q1. DBSCAN Clustering
- Q2. How does current work helps solving use cases for PayU
- Ans.
My current work involves analyzing transaction data to identify patterns and trends, which can help PayU optimize their payment processing services.
Analyzing transaction data to identify fraudulent activities and improve security measures for PayU
Developing predictive models to forecast transaction volumes and optimize payment processing times
Utilizing machine learning algorithms to personalize user experiences and inc...
InfoOnly
I applied via Referral and was interviewed in May 2024. There was 1 interview round.
(2 Questions)
- Q1. Why are you interested in this role
- Q2. Provide an example how you solved a problem
- Ans.
I solved a problem by using machine learning algorithms to predict customer churn for a telecom company.
Identified relevant data sources such as customer demographics, usage patterns, and customer service interactions.
Preprocessed and cleaned the data to handle missing values and outliers.
Built and trained a machine learning model using algorithms like logistic regression and random forest.
Evaluated the model's perform...
Niharika
Selected
I applied via Company Website and was interviewed before May 2023. There was 1 interview round.
(2 Questions)
- Q1. Projects Mentioned in Resume
- Q2. Related to Python, Pyspark
Selected
I applied via campus placement at Lovely Professional University (LPU) and was interviewed before Jul 2023. There were 4 interview rounds.
Basic questions like stats, probability etc
Scenario based question
(1 Question)
- Q1. Questions on fundamentals
(1 Question)
- Q1. General questions
Akshay Agrawal
I applied via LinkedIn and was interviewed in Jun 2022. There were 2 interview rounds.
(3 Questions)
- Q1. What is rnn and lstm
- Ans.
RNN stands for Recurrent Neural Network and LSTM stands for Long Short-Term Memory. They are types of neural networks used for sequential data processing.
RNN is a type of neural network that can process sequential data by maintaining a memory of past inputs.
LSTM is a type of RNN that can handle the vanishing gradient problem and can remember long-term dependencies.
LSTM has gates that control the flow of information int...
- Q2. What is precision and recall
- Ans.
Precision and recall are two important metrics used to evaluate the performance of a classification model.
Precision measures the proportion of true positives among all the predicted positives.
Recall measures the proportion of true positives among all the actual positives.
Precision and recall are inversely related and a trade-off exists between them.
A high precision means that the model is good at predicting positive ca...
- Q3. What is regularisation
- Ans.
Regularisation is a technique used in machine learning to prevent overfitting by adding a penalty term to the loss function.
Regularisation helps to control the complexity of a model and reduce the impact of irrelevant features.
It adds a penalty term to the loss function, which encourages the model to have smaller weights.
There are different types of regularisation techniques such as L1 (Lasso) and L2 (Ridge) regularisa...
Interview Preparation Tips
- Deep Learning
- Machine Learning
- SQL
- Python
Skills evaluated in this interview
(2 Questions)
- Q1. When is your Availability
- Q2. Expectation from us
- Ans.
I expect a supportive work environment, opportunities for growth, and clear communication.
Clear communication on project goals and expectations
Opportunities for professional development and growth
Supportive team environment
Regular feedback and performance evaluations
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