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Ideapoke Technologies Data Science Intern Interview Questions and Answers
Ideapoke Technologies Data Science Intern Interview Experiences
1 interview found
Arun Kumar
Selected
I applied via Approached by Company and was interviewed in Dec 2023. There were 2 interview rounds.
Coding assignment was given to make a document summarizer and to get answer to questions from a text documents which were company reports using OpenAI api and langchain and finally publishing an Fastapi API to test it on postman
(4 Questions)
- Q1. Tell me about yourself?
- Ans.
I am a data science enthusiast with a strong background in statistics and machine learning.
Completed a Bachelor's degree in Statistics
Proficient in programming languages like Python and R
Experience with data visualization tools like Tableau
Completed projects involving predictive modeling and data analysis
- Q2. From where did you complete the Data Science course?
- Ans.
I completed the Data Science course at XYZ University.
Completed Data Science course at XYZ University
Received hands-on training in machine learning algorithms
Worked on real-world projects during the course
- Q3. Why there is career gap after postgraduation?
- Ans.
Career gaps after postgraduation can be due to various reasons such as personal reasons, further education, job search challenges, or health issues.
Personal reasons such as family responsibilities, relocation, or taking time off to travel
Pursuing further education or certifications to enhance skills and knowledge
Challenges in finding suitable job opportunities in a competitive market
Health issues or personal circumstan
- Q4. What technologies do you know?
- Ans.
I am familiar with a variety of technologies commonly used in data science, including programming languages, databases, and machine learning tools.
Programming languages: Python, R, SQL
Databases: MySQL, MongoDB
Machine learning tools: TensorFlow, scikit-learn
Interview Preparation Tips
- Openai
- Generative ai
- Python
- OOPS
- fastapi
- Langchain
- NLP
- summarization
Skills evaluated in this interview
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Interview questions from similar companies
Anonymous
(2 Questions)
- Q1. What is overfitting in machine learning?
- Ans.
Overfitting occurs when a machine learning model learns the training data too well, including noise and outliers, leading to poor generalization on new data.
Overfitting happens when a model is too complex and captures noise in the training data.
It leads to poor performance on unseen data as the model fails to generalize well.
Techniques to prevent overfitting include cross-validation, regularization, and early stopping.
...
- Q2. Overfitting accurs when a model learns the details.......etc
- Ans.
Overfitting occurs when a model learns the details and noise in the training data to the extent that it negatively impacts the model's performance on new data.
Overfitting happens when a model is too complex and captures noise in the training data.
It leads to poor generalization and high accuracy on training data but low accuracy on new data.
Techniques to prevent overfitting include cross-validation, regularization, and...
Interview Preparation Tips
Forecasting problem - Predict daily sku level sales
(2 Questions)
- Q1. What is difference between bias and variance
- Ans.
Bias is error due to overly simplistic assumptions, variance is error due to overly complex models.
Bias is the error introduced by approximating a real-world problem, leading to underfitting.
Variance is the error introduced by modeling the noise in the training data, leading to overfitting.
High bias can cause a model to miss relevant relationships between features and target variable.
High variance can cause a model to ...
- Q2. Parametric vs non parametruc model
- Ans.
Parametric models make strong assumptions about the form of the underlying data distribution, while non-parametric models do not.
Parametric models have a fixed number of parameters, while non-parametric models have a flexible number of parameters.
Parametric models are simpler and easier to interpret, while non-parametric models are more flexible and can capture complex patterns in data.
Examples of parametric models inc...
Skills evaluated in this interview
I applied via Naukri.com and was interviewed before Mar 2023. There were 3 interview rounds.
(1 Question)
- Q1. Machine Learning
(1 Question)
- Q1. Machine Learning
Approach check for multiple case studies
Interview Preparation Tips
Data Scientist Interview Questions & Answers
Thinkitive Technologies
Ganesh Patil
posted on 29 Feb 2024
Selected
I applied via Approached by Company and was interviewed before Mar 2023. There were 3 interview rounds.
(1 Question)
- Q1. Mostly about projects ml, nlp, python code would be asked
(1 Question)
- Q1. It would be focused on technical stuff in detail ml, nlp, deployments etc
(1 Question)
- Q1. Organisation fit
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Ideapoke Technologies Data Science Intern Interview Process
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