PureSoftware Data Scientist Interview Questions and Answers

Q1. Data science related areas
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Case study related to semantic search

Q1. Questions based on case study
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Q1. Question regarding nlp,python,ml
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Q1. Machine Learning algorithms
Ans. 
Machine Learning algorithms are used to train models on data to make predictions or decisions without being explicitly programmed.
• Machine Learning algorithms can be categorized into supervised, unsupervised, and reinforcement learning.

• Examples of supervised learning algorithms include linear regression, decision trees, and support vector machines.

• Examples of unsupervised learning algorithms include k-means clustering, ...read more
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Q2. Overfitting and underfitting
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Q3. Questions related to the project
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Q1. Questions on project, how much time required for training model
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Q2. Version control, Flask/ Django, Cloud service experience
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Q1. Tell me about scaling. ensemble techniques. precession, recall, f1 score, ROC AUC LSTM and RNN Feature selection and extraction optimization function loss functions word embedding word2vec tf-idf outliers...read more
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Q1. Concepts and tools
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Coding on the tools we use

Q1. Not cleared the round
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Q1. General ML questions
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Q2. General dl. Questions
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Q1. Questions around the previous work
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Q2. Questions around how re-rank work, and image segmentation,
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Q3. Questions with podman and docker
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Q1. Project that I worked on
Ans. 
Developed a predictive model for customer churn in a telecom company
• Used machine learning algorithms like logistic regression and random forest

• Analyzed customer data such as call duration, plan details, and customer complaints

• Achieved 85% accuracy in predicting customer churn
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Q2. Use case only verbal communication
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