ZF India Technology Center Data Scientist Interview Questions and Answers

Q1. What is difference between lstm and rnn
Ans. 
LSTM is a type of RNN that addresses the vanishing gradient problem by using memory cells.
• RNN stands for Recurrent Neural Network, a type of neural network that processes sequential data.

• LSTM stands for Long Short-Term Memory, a type of RNN that includes memory cells to retain information over long sequences.

• LSTM is designed to overcome the vanishing gradient problem, which occurs when training RNNs on long sequences.

• L...read more
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Q1. What are different evaluation matrix ?
Ans. 
Evaluation matrices are used to assess the performance of models in data science.
• Confusion matrix: used to evaluate the performance of classification models.

• Precision, recall, and F1 score: measures for binary classification models.

• Mean squared error (MSE): evaluates the performance of regression models.

• R-squared: assesses the goodness of fit for regression models.

• Area under the ROC curve (AUC-ROC): evaluates the perfo...read more
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Q1. Tell me about yourself
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Q2. Questions from projects which was mentioned on resume
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Q1. Fitment based questions
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Q2. Explain a project
Ans. 
Developed a machine learning model to predict customer churn for a telecom company.
• Collected and cleaned customer data including usage patterns and demographics

• Used classification algorithms like Random Forest and Logistic Regression to build the model

• Evaluated model performance using metrics like accuracy, precision, and recall
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Math, English, reasoning

Q1. Asked me about expected salary
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Q1. 2 round technical interview, both of them about ML and last one concerning statistics and ML.
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Q2. What is linear regression?
Ans. 
Linear regression is a statistical method to model the relationship between a dependent variable and one or more independent variables.
• It assumes a linear relationship between the variables

• It is used to predict the value of the dependent variable based on the independent variable(s)

• It can be simple linear regression (one independent variable) or multiple linear regression (more than one independent variable)

• It is commo...read more
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Q3. Question regarding confusion matrix?
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Q4. Name various ML algorithm?
Ans. 
ML algorithms are used to train models on data to make predictions or decisions. Some popular ones are SVM, KNN, and Random Forest.
• Support Vector Machines (SVM)

• K-Nearest Neighbors (KNN)

• Random Forest

• Naive Bayes

• Decision Trees

• Linear Regression

• Logistic Regression

• Neural Networks

• Gradient Boosting

• Clustering Algorithms (K-Means, Hierarchical)

• Association Rule Learning (Apriori)

• Dimensionality Reduction Algorithms (PCA, LDA)

• Reinf
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Q1. What is overfitting and underfitting
Ans. 
Overfitting occurs when a model learns the training data too well, leading to poor performance on new data. Underfitting occurs when a model is too simple to capture the underlying patterns in the data.
• Overfitting: Model is too complex, fits noise in the training data, performs poorly on new data

• Underfitting: Model is too simple, fails to capture underlying patterns in the data, performs poorly on both training and new...read more
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Q2. What are LLM Models
Ans. 
LLM models, or Language Model Models, are a type of machine learning model that focuses on predicting the next word in a sequence of words.
• LLM models are commonly used in natural language processing tasks such as text generation, machine translation, and speech recognition.

• They are trained on large amounts of text data to learn the relationships between words and predict the most likely next word in a given context.

• Exa...read more
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