Ninestars Information Technologies Data Scientist Interview Questions and Answers

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. Basic ML Question, Timesereis and RNN with some questions on Comp Vision
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Q1. Project driven. Some coding
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Q1. Salary Discussion
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Q1. Question regarding nlp,python,ml
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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. Tell me about yourself
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Q2. Give me project details
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Aptitude test all mathematical and general aptitude questions

Any topic related to current trends

Q1. Totally technical round all the questions related to the position that you are applying for
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Q2. Different types of Models etc..
Ans. 
There are various types of models used in different fields such as statistical models, mathematical models, physical models, etc.
• Statistical models: Used in data analysis to make predictions or draw inferences.

• Mathematical models: Represented using mathematical equations to describe real-world phenomena.

• Physical models: Used to simulate physical systems or objects for testing or analysis.

• Computer models: Utilized in co...read more
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Q3. Explain Bug life cycle or defect life cycle
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Bug life cycle or defect life cycle is the process of identifying, reporting, prioritizing, fixing, and verifying bugs in software development.
• Bug identification: Bugs are identified through testing, user feedback, or code reviews.

• Bug reporting: Bugs are reported in a bug tracking system with details like steps to reproduce, severity, and priority.

• Bug prioritization: Bugs are prioritized based on severity and impact on...read more
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Q1. Core python,python library and data science
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Q1. Mathematics,python and sql and data science are complete
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Q1. Why did we hired you
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Q2. What is next 5 years see your self
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